Screening programmes for the early detection and prevention of oral cancer

  • Review
  • Intervention

Authors


Abstract

Background

Oral cancer is an important global healthcare problem, its incidence is increasing and late-stage presentation is common. Screening programmes have been introduced for a number of major cancers and have proved effective in their early detection. Given the high morbidity and mortality rates associated with oral cancer, there is a need to determine the effectiveness of a screening programme for this disease, either as a targeted, opportunistic or population-based measure. Evidence exists from modelled data that a visual oral examination of high-risk individuals may be a cost-effective screening strategy and the development and use of adjunctive aids and biomarkers is becoming increasingly common.

Objectives

To assess the effectiveness of current screening methods in decreasing oral cancer mortality.

Search methods

We searched the following electronic databases: the Cochrane Oral Health Group's Trials Register (to 22 July 2013), the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2013, Issue 6), MEDLINE via OVID (1946 to 22 July 2013), EMBASE via OVID (1980 to 22 July 2013) and CANCERLIT via PubMed (1950 to 22 July 2013). There were no restrictions on language in the search of the electronic databases.

Selection criteria

Randomised controlled trials (RCTs) of screening for oral cancer or potentially malignant disorders using visual examination, toluidine blue, fluorescence imaging or brush biopsy.

Data collection and analysis

Two review authors screened the results of the searches against inclusion criteria, extracted data and assessed risk of bias independently and in duplicate. We used mean differences (MDs) and 95% confidence intervals (CIs) for continuous data and risk ratios (RRs) with 95% CIs for dichotomous data. Meta-analyses would have been undertaken using a random-effects model if the number of studies had exceeded a minimum of three. Study authors were contacted where possible and where deemed necessary for missing information.

Main results

A total of 3239 citations were identified through the searches. Only one RCT, with 15-year follow-up met the inclusion criteria (n = 13 clusters: 191,873 participants). There was no statistically significant difference in the oral cancer mortality rates for the screened group (15.4/100,000 person-years) and the control group (17.1/100,000 person-years), with a RR of 0.88 (95% CI 0.69 to 1.12). A 24% reduction in mortality was reported between the screening group (30/100,000 person-years) and the control group (39.0/100,000) for high-risk individuals who used tobacco or alcohol or both, which was statistically significant (RR 0.76; 95% CI 0.60 to 0.97). No statistically significant differences were found for incidence rates. A statistically significant reduction in the number of individuals diagnosed with stage III or worse oral cancer was found for those in the screening group (RR 0.81; 95% CI 0.70 to 0.93). No harms were reported. The study was assessed as at high risk of bias.

Authors' conclusions

There is evidence that a visual examination as part of a population-based screening programme reduces the mortality rate of oral cancer in high-risk individuals. In addition, there is a stage shift and improvement in survival rates across the population as a whole. However, the evidence is limited to one study, which has a high risk of bias and did not account for the effect of cluster randomisation in the analysis. There was no evidence to support the use of adjunctive technologies like toluidine blue, brush biopsy or fluorescence imaging as a screening tool to reduce oral cancer mortality. Further RCTs are recommended to assess the efficacy and cost-effectiveness of a visual examination as part of a population-based screening programme in low, middle and high-income countries.

Résumé scientifique

Les programmes de dépistage pour la détection précoce et la prévention du cancer buccal

Contexte

Le cancer buccal est un problème de santé important mondialement, son incidence est en augmentation et la détection en stade de développement avancé est fréquente. Les programmes de dépistage ont été introduits pour un certain nombre de cancers majeurs et se sont avérés efficaces pour la détection précoce. Compte-tenu de la morbidité et des taux de mortalité associés au cancer buccal, il est nécessaire de déterminer l'efficacité d'un programme de dépistage pour cette maladie, soit ciblé, soit opportuniste, ou comme mesure basée sur la population. Il existe des preuves issues de données modélisées qu'un examen buccal visuel des personnes à haut risque pourrait être une stratégie de dépistage rentable. De plus, le développement et l'utilisation d'aides complémentaires et de bio-marqueurs sont de plus en plus fréquents.

Objectifs

Évaluer l'efficacité des méthodes de dépistage actuelles pour réduire la mortalité par cancer buccal.

Stratégie de recherche documentaire

Nous avons effectué des recherches dans les bases de données électroniques suivantes : le registre des essais cliniques du groupe Cochrane sur la santé bucco-dentaire (jusqu' au 22 juillet 2013), le registre Cochrane des essais contrôlés (CENTRAL) ( La Bibliothèque Cochrane 2013, numéro 6), MEDLINE via OVID (de 1946 au 22 juillet 2013), EMBASE via OVID (de 1980 au 22 juillet 2013) et CANCERLIT via PubMed (de 1950 jusqu' au 22 juillet 2013). Aucune restriction de langue dans les recherches effectuées sur les bases de données électroniques n’a été appliquée.

Critères de sélection

Essais contrôlés randomisés (ECR) sur le dépistage du cancer buccal ou des troubles potentiellement malins à l'aide d'un examen visuel, du bleu de toluidine, de l'imagerie fluorescence ou de la biopsie par brossage.

Recueil et analyse des données

Deux auteurs de la revue ont passé au crible les résultats des recherches par rapport aux critères d'inclusion, extrait les données et évalué le risque de biais de manière indépendante et en double. Nous avons utilisé la différence moyenne (DM) et les intervalles de confiance (IC) à 95% pour les données continues et les risques relatifs (RR) avec IC à 95% pour les données dichotomiques. Les méta-analyses auraient été réalisées à l'aide d'un modèle à effets aléatoires si le nombre d'études dépassait un minimum de trois. Les auteurs des études ont été contactés lorsque cela était possible et jugé nécessaire pour obtenir des informations manquantes.

Résultats principaux

Un total de 3 239 références bibliographiques a été identifié par les recherches. Un seul ECR, avec un suivi sur 15 ans, remplissait les critères d'inclusion (n =13 grappes : 191 873 participants). Il n'y avait aucune différence statistiquement significative concernant le taux de mortalité par cancer buccal dans le groupe de dépistage (15,4/100,000 personne-années) et le groupe témoin (17,1/100,000 personne-années), avec un RR de 0,88 (IC à 95% de 0,69 à 1,12). 24% de réduction de la mortalité était rapportée entre le groupe de dépistage (30/100,000 personne-années) et le groupe témoin (39,0/100,000) pour les sujets à haut risque, qui consommaient du tabac ou de l'alcool ou les deux, ce qui était statistiquement significatif (RR 0,76; IC à 95% de 0,60 à 0,97). Aucune différence statistiquement significative n'a été trouvée pour les taux d'incidence. Une réduction statistiquement significative dans le nombre d'individus présentant un diagnostic de stade III ou une aggravation de cancer buccal a été trouvée chez les patients du groupe de dépistage (RR 0,81; IC à 95% de 0,70 à 0,93). Aucun préjudice n'a été signalé. L'étude a été évaluée comme présentant un risque de biais élevé.

Conclusions des auteurs

Il existe des preuves indiquant qu'un examen visuel, dans le cadre d'un programme de dépistage, réduit le taux de mortalité de cancer buccal chez les sujets à haut risque. De plus, les taux de survie à travers la population mondiale se sont améliorés. Cependant, les preuves sont limitées à une étude qui a un risque de biais élevé. Dans l'analyse, les preuves n'ont également pas pris en compte l'effet de la randomisation en groupes. Il n'y avait aucune preuve permettant de recommander l'utilisation de technologies complémentaires, telles que le bleu de toluidine, la biopsie par brossage ou l'imagerie médicale fluorescence comme outil de dépistage pour réduire la mortalité par cancer buccal. D’autres ECR sont recommandés pour évaluer l'efficacité et la rentabilité d'un examen visuel dans le cadre d'un programme de dépistage dans les pays à revenus faibles, moyens et élevés.

摘要

口腔癌的早期偵測與預防之篩檢方案

背景

口腔癌是一個重要的全球健康問題,它的發生率正在增加當中且常見於後期才有明顯表徵的情形。篩檢方案已經導入在許多主要的癌症上,也已經證明對於癌症的早期偵測是有效的。有鑒於與口腔癌相關的高發病率與高死亡率,判斷這個疾病的篩檢方案之有效性是必要的,不論是做為一個針對特定目標的、伺機性的或以族群為基礎的量度。模型化資料中的證據顯示,口腔黏膜目視檢查對屬於高危險群的個體來說,可能是一個符合經濟效益的篩檢策略,且輔助工具與生物標記的開發及使用也變得越來越普遍。

目的

評估現行篩檢方法對於降低口腔癌死亡率的效益。

搜尋策略

我們搜尋了下列的電子資料庫:Cochrane Oral Health Group's Trials Register (至2013年7月22日)、Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2013年,Issue 6)、MEDLINE via OVID (1946年至2013年7月22日)、EMBASE via OVID (1980年至2013年7月22日)以及CANCERLIT via PubMed (1950年至2013年7月22日)等資料庫;在搜尋電子資料庫時,沒有語言上的限制。

選擇標準

以目視檢查、甲苯胺藍染色、螢光顯影或刷抹切片,進行口腔癌或潛在惡性病篩檢的隨機對照試驗(RCTs)。

資料收集與分析

兩位作者獨立且重複地篩檢搜尋與納入條件比較的結果、摘錄資料並評估偏誤風險。我們針對連續數據使用平均差(MD)與95%信賴區間(CIs),而二分資料則使用風險率比(RR)與95% CIs。如果研究數量為四個以上,統合分析可能會是以隨機效應模式進行。資訊遺漏時,在有辦法或認為必要的情況下,會連絡研究作者。

主要結果

在搜尋過程中,共找出3,239篇引文,只有一個追蹤了15年的RCT符合納入條件(n = 13個群組:191,873位受試者)。在篩檢組(15.4/100,000人-年)與對照組(17.1/100,000人-年)中,口腔癌死亡率沒有統計上的顯著差異,RR皆為0.88(95% CI 0.69至1.12)。抽菸、喝酒或兩者皆有的高危險群個體,在篩檢組(30/100,000人-年)及對照組(39.0/100,000人-年)中皆有死亡率減少24%的記錄(RR 0.76; 95% CI 0.60至0.97),這在統計上是重要的;在發生率上則沒有發現有統計上的顯著差異。在篩檢組中發現,被診斷為第三期或更嚴重的口腔癌患者人數有統計上的顯著減少(RR 0.81; 95% CI 0.70至0.93)。沒有損害的記錄,本研究被評估為高偏誤風險。

作者結論

有證據顯示,在以族群為基礎的篩檢方案中,目視檢查能降低口腔癌高危險群個體的死亡率。此外,在所有的人當中,也能轉換口腔癌的分期與改善存活率。然而,此證據只侷限於一個研究,有高偏誤風險且無法說明對於分析中以群組為單位隨機分派的影響。沒有證據支持使用像甲苯胺藍染色、刷抹切片或螢光顯影為篩檢工具的輔助技術能降低口腔癌死亡率;建議要有更進一步的RCTs,評估在低、中、高收入國家中,目視檢查在以族群為基礎的篩檢方案裡的功效與經濟效益。

譯註

翻譯者:臺北醫學大學考科藍臺灣研究中心(Cochrane Taiwan)

本翻譯計畫由臺北醫學大學考科藍臺灣研究中心(Cochrane Taiwan)、台灣實證醫學學會及東亞考科藍聯盟(EACA)統籌執行
聯絡E-mail:cochranetaiwan@tmu.edu.tw

Plain language summary

Screening programmes for the early detection and prevention of oral cancer

Review question

This review, carried out by authors of the Cochrane Oral Health Group, was conducted to investigate the effectiveness of current screening programmes in detecting oral cancer at an early stage and whether or not they can assist in decreasing deaths due to oral cancer.

Background

Oral cancer is increasing worldwide and it is the sixth most common cancer overall. The highest rates of oral cancer occur in the most disadvantaged sections of the population. Important risk factors in the development of the disease are tobacco, alcohol, age, gender and sunlight although a role for candida (which causes thrush) and the human papillomavirus (which causes warts) has also been documented. People who are heavy drinkers and also smoke have 38 times the risk of developing oral cancer compared with people who do neither. These factors are considered to be especially important in the development of the disease in young people, a group experiencing an increasing incidence of the disease, particularly in countries with a high incidence of it.

Geographic variation in the occurrence of oral cancer around the world is wide. For example it is the most common cancer for men in India, Sri Lanka and Pakistan and 30% of all new cases of cancer in these countries is oral cancer whereas only 3% of new cases of cancer in the United Kingdom are oral cancer.

When people first seek medical help, their oral cancer is usually at a late or advanced stage and the effects of the condition as well as the treatment for it can be extremely debilitating. Death rates from oral cancer and the negative effects of the disease are high and increasing rather than declining as for other cancers such as breast and colon.

Prevention screening programmes for other cancers have proven to be effective in early detection. However, whilst there maybe advantages to screening there are disadvantages because screening has the potential to produce either false positive or false negative results. Screening can be targeted at high-risk groups, it can be opportunistic, for example when people attend health services for other reasons, or can be done by looking at statistics across the population as a whole.

The aim of preventive screening for early detection of oral cancer is to screen individuals for pre-cancerous conditions which are lesions such as leukoplakia. The most common screening method is visual inspection by a clinician but other techniques include the use of a special blue dye, the use of imaging techniques and measuring biochemical changes to normal calls.

Study characteristics

The evidence on which this review is based is up to date as of 22 July 2013. The only study included was based in rural areas of the city of Trivandrum in Kerala, India. The study included 191,873 apparently healthy adults aged 35 years or older living in 13 clusters with an average of 14,759 participants in each cluster. Screening took place in seven clusters (96,517 participants) and six clusters acted as a control (95,356 participants). Participants were excluded if they were bedridden, if they had open tuberculosis, other debilitating diseases or were already suffering from oral cancer.

Healthcare workers trained in the detection of oral lesions undertook the screening of participants and the social history of participants including use of paan, tobacco, alcohol and dietary supplements was recorded.

Key results

The review found that overall there is not enough evidence to decide whether screening by visual inspection reduces the death rate for oral cancer and there is no evidence for other screening methods. However, there is some evidence that it might help reduce death rates in patients who use tobacco and alcohol although the only included study may be affected by bias.

Quality of evidence

The evidence presented is of low quality and limited to one study assessed as at high risk of bias.

Résumé simplifié

Les programmes de dépistage pour la détection précoce et la prévention du cancer buccal

Question

Cette revue, menée par les auteurs du groupe Cochrane sur la santé bucco-dentaire, a été effectuée pour examiner l'efficacité des programmes actuels de dépistage dans la détection de cancer buccal à un stade précoce et s’ils peuvent ou non aider à réduire les décès dus au cancer buccal.

Contexte

Le cancer buccal est en augmentation dans le monde et il s’agit du sixième cancer le plus fréquent. Les plus fort taux de cancers buccaux surviennent dans les populations les plus défavorisées. Les facteurs de risque importants dans le développement de la maladie sont le tabac, la consommation d'alcool, l'âge, le sexe et la lumière du soleil, bien que la candidose (provoquant des mycoses) et le virus du papillome humain (provoquant des verrues) aient également été rapportés. Les personnes qui sont fumeurs et consommateurs excessifs d'alcool ont un risque38 fois supérieurs de développer un cancer buccal par rapport aux non-fumeurs ne consommant pas d’alcool. Ces facteurs sont considérés être particulièrement important chez les jeunes dans le développement de la maladie, un groupe de patients éprouvant une incidence accrue de la maladie, en particulier dans les pays à une incidence élevée du cancer buccal.

Les variations géographiques à travers le monde dans les cas de cancers buccaux sont larges. Par exemple, c’est le cancer le plus fréquent chez les hommes en Inde, au Sri Lanka et au Pakistan et 30% de tous les nouveaux cas de cancers dans ces pays sont des cancers buccaux, tandis que seulement 3% de nouveaux cas de cancers au Royaume-Uni sont des cancers buccaux.

Lors d’une première évaluation médicale, le cancer buccal est généralement à un stade avancé ou tardif. De plus, les effets de la maladie, et du traitement peuvent être extrêmement débilitants. Les taux de mortalité par cancer buccal et les effets néfastes de la maladie sont élevés et en hausse, plutôt qu’en déclin, tels que les cancers du sein et du côlon.

Les programmes de dépistages préventifs concernant d'autres cancers se sont avérés être efficaces pour la détection précoce. Cependant, alors qu'il peut être bénéfique de dépister, il existe des inconvénients, car le dépistage peut fournir de faux résultats positifs ou négatifs. Le dépistage peut cibler les groupes à haut risque, il peut être opportuniste, par exemple lorsque les personnes ont recours aux services de santé pour d'autres raisons, ou peut être réalisé en étudiant les statistiques parmi la population dans son ensemble.

L'objectif du dépistage préventif pour la détection précoce de cancer buccal est d'identifier les individus avec des pathologies précancéreuses qui sont des lésions, telles que la leucoplasie. La méthode de dépistage la plus courante est un examen visuel par un clinicien, mais d'autres techniques incluent l'utilisation d'un colorant spécial de couleur bleue, l'utilisation de techniques d'imagerie et la mesure des changements biochimiques.

Les caractéristiques de l'étude

Les preuves sur lesquelles cette revue est basée ont été mise à jour le 22 juillet 2013. La seule étude incluse a été réalisée dans des zones rurales de Trivandrum dans le Kerala, en Inde. L'étude incluait 191 873 adultes apparemment en bonne santé, âgés de 35 ans ou plus. Elle comportait 13 groupes avec une moyenne de 14 759 participants dans chaque groupe. Le dépistage s’est déroulé dans sept groupes (96 517 participants), les six autres étaient des groupes témoins (95 356 participants). Les personnes invalides, qui allaitaient, qui souffraient d’une tuberculose ouverte ou d’une autre maladie débilitante ou qui étaient déjà atteintes du cancer buccal, ont été exclues.

Les professionnels de santé, formés dans la détection de lésions orales, ont dépisté les participants. De plus, les antécédents sociaux des participants, dont la consommation de tabac, d'alcool, de noix de bétel et de compléments alimentaires ont été enregistrés.

Résultats principaux

Cette revue a constaté que, globalement, il n'existe pas suffisamment de preuves pour déterminer si le dépistage, par un examen visuel, réduit le taux de mortalité pour un cancer buccal et il n'existe pas de preuves pour d'autres méthodes de dépistage. Cependant, certaines preuves démontrent qu'il pourrait permettre de réduire les taux de mortalité chez les consommateurs de tabac et d'alcool bien que la seule étude incluse puisse être affectée par un biais.

La qualité des preuves

Les preuves présentées sont de faible qualité et limitées à une étude évaluée comme présentant un risque de biais élevé.

Notes de traduction

Traduit par: French Cochrane Centre 14th January, 2014
Traduction financée par: Minist�re Fran�ais des Affaires sociales et de la Sant�, Instituts de Recherche en Sant� du Canada, Minist�re de la Sant� et des Services Sociaux du Qu�bec, Fonds de recherche du Qu�bec Sant� et Institut National d'Excellence en Sant� et en Services Sociaux

淺顯易懂的口語結論

口腔癌的早期偵測與預防之篩檢方案

文獻問題

本文獻由Cochrane Oral Health Group的作者們完成,是為了研究現行篩檢方案對早期發現口腔癌的有效性與是否能協助降低口腔癌造成的死亡而進行。

背景

口腔癌正在世界各地增加當中,且整體來說,它高居最常見癌症的第六位。在社經地位最弱勢的族群中,口腔癌的發生率為最高。形成此疾病的重要危險因子有菸、酒、年齡、性別以及陽光,然而念珠菌(導致鵝口瘡的產生)與人類乳突病毒(導致疣的產生)也曾被記載。重度酗酒且抽菸的人,罹患口腔癌的風險為不菸不酒的人的38倍。特別在發生率高的國家中,這些都被視為造成此疾病在年輕人身上(一個正在經歷口腔癌發生率增加的族群)形成的極度重要因子。

世界各地發生口腔癌的地理變異很廣,舉例來說,對印度、斯里蘭卡與巴基斯坦的男人來說,這是最常見的癌症;這些國家所有新的癌症案例中有30%是口腔癌,而在英國所有新的癌症案例中,只有3%為口腔癌。

人們首次尋求醫療協助時,他們的口腔癌通常已經是晚期或後期,此時的病況以及相應的治療可能會使患者更加虛弱。口腔癌死亡率與此疾病的負面效應高並且還在增加中,不像其他癌症(如:乳癌與結腸癌)一樣在降低當中。

其他癌症的預防篩檢方案已經證明對早期偵測是有效的。然而,雖然篩檢可能有好處但也可能有缺點,因為篩檢有產生偽陽性或偽陰性結果的潛在可能。可以針對高危險群做篩檢,也可以伺機,例如在當人們為了其他原因而使用醫療服務時執行,或者在檢視所有人的統計資料後進行篩檢。

口腔癌早期偵測的預防篩檢,目標是為了偵測出癌症前期的症狀,也就是像白斑病這樣的病灶,而做的個體篩檢。最常見的篩檢方法是由臨床醫師進行目視檢查,其他技術則包括特殊藍色染劑的使用、顯影技術的使用與測量正常細胞的生物化學變化。

研究特性

本文獻的根據為至2013年7月22日的最新證據。唯一收錄的研究之根據地,是在印度喀拉拉邦郊區的特里凡德琅市。研究包括191,873位顯然為健康、35歲或以上且居住在13個平均有14,759位受試者的群體中之成人。篩檢在7個群體中進行(96,517位受試者),有6個群體為對照組(95,356位受試者);排除久病、有開放性結核、其他會使其衰弱的疾病或已罹患口腔癌的受試者。

由接受過口腔病灶偵測訓練的健康照護工作人員來進行受試者的篩檢,且受試者的社交生活史,包括嚼檳榔、抽菸、喝酒與膳食補充品的攝取皆被記錄。

主要結論

本文發現整體來說,沒有足夠的證據判定以目視檢查做的篩檢是否能降低口腔癌死亡率,且沒有關於其他篩檢方法的證據。然而,儘管唯一收錄的研究可能受偏誤影響,在有抽菸喝酒的患者中,有些證據仍顯示它也許能幫助降低死亡率。

證據品質

提出來的證據品質為低,且受限於一個被評估為高偏誤風險的研究。

譯註

翻譯者:臺北醫學大學考科藍臺灣研究中心(Cochrane Taiwan)

本翻譯計畫由臺北醫學大學考科藍臺灣研究中心(Cochrane Taiwan)、台灣實證醫學學會及東亞考科藍聯盟(EACA)統籌執行
聯絡E-mail:cochranetaiwan@tmu.edu.tw

Background

Description of the condition

Oral cancer is the sixth most common cancer globally and represents a group of conditions with a range of sites and a varied aetiology. Its annual estimated incidence is approximately 275,000, but unlike many other cancers, its incidence is increasing (Warnakulasuriya 2009). There is a wide geographic variation in the incidence of the disease with two-thirds of the burden born by low-income and middle-income countries from South and South-East Asia, Latin America and Eastern Europe. However, the incidence continues to rise in the West (IARC 2010) and the age standardised incidence of oral cancer in Western Europe has steadily increased over the past two decades (Boyle 2005). Within the European Union countries, the highest male incidence rates are found in France and Hungary, whilst the lowest rates are found in Greece and Cyprus (IARC 2010). India, Sri Lanka and Pakistan have the highest levels of disease, making it the most common cancer for men in these countries and accounts for up to 30% of all new cases of cancer compared to 3% in the United Kingdom (UK) and 6% in France (Cancer Research UK). The age-adjusted incidence rate from these countries cancer registries range from 3.4 to 13.8 per 100,000 (Ministry of Health 2005; Warnakulasuriya 2009). The incidence of oral cancer for men in Brazil is second only to France and India with an estimated crude rate of 11 per 100,000. In the UK, the incidence of oral cancer is increasing (Conway 2006; Doobaree 2009) and 6236 cases of oral cancer were diagnosed in 2009 (Cancer Research UK). This represents a doubling of the number of cases seen in 1989 and represents a year on year increase of approximately 2.7% per year (Warnakulasuriya 2009). The incidence of oral cancer is strongly associated with social and economic deprivation (Scully 2009; Conway 2010a), with the highest rates occurring in the most disadvantaged sections of the population. Across Europe, inequalities tend to be observed among men, particularly in the UK and Eastern Europe (Conway 2010b).

Important risk factors in the development of the disease are tobacco, betel quid, alcohol, age, gender and sunlight. More recently, a role for candida and the human papillomavirus (HPV) has been documented (Scully 2009). Epidemiological evidence from US populations indicates a strong association between HPV and oropharyngeal cancers (Cleveland 2011). Incidence of HPV globally is unknown but thought to be rising, but estimates from the United States of America (USA) show a substantial increase of HPV-positive oropharyngeal cancers, rising by 225% in the period between 1984 and 2004 (Sanders 2011). Increased consumption of alcohol has been implicated in the increasing incidence of the disease in the UK (Hindle 2000) at a time when tobacco use is falling (Ogden 2005), although the precise mechanism remains unclear (Ogden 1998). Heavy drinkers and smokers have 38 times the risk of developing oral cancer compared to abstainers (Blot 1988). This is thought to be due to acetaldehyde, the first metabolite of alcohol, which is classified as a Group 1 carcinogen and is also present in tobacco (Salaspuro 2011). Historically, the risk of developing oral cancer increased with age, however, the age group with the highest incidence (26.8%) in the USA between 2003 and 2007 was between 55 and 64 years of age (SEER 2010). In contrast, many patients from high-incidence countries are below the age of 40 years of age (Warnakulasuriya 2009).

Of equal concern to the increasing incidence, is the lack of any change in the age-standardised mortality rates, despite advances in surgical and management techniques. This is unlike the falling rates for cancer of the breast and colon (Cancer Research UK). The five-year survival rates for oral cancer for most countries is approximately 50% (Warnakulasuriya 2009). These have been estimated at 3 to 4 per 100,000 men and 1.5 to 2.0 per 100,000 for women respectively (Warnakulasuriya 2009). Mortality rates from oral cancer have also increased in certain European countries (La Vecchia 2004). The most important determinant factor in cancer survival is diagnostic delay (Onizawa 2003; McLeod 2005), as over 60% of patients present with stage III and IV disease (Lingen 2008), meaning that their management is complex and multidisciplinary. The stage at diagnosis significantly affects five-year survival, with survival rates approaching 80% for stage I disease, whilst dropping significantly for stage IV disease (Rusthoven 2010). In addition, the morbidity associated with surgery is high, the rate of second primary tumours is greater than any other type of cancer (3% to 7% per annum) (Day 1992) and is more often the cause of death (Lippman 1989).

Description of the intervention

Prevention strategies are important to meet the World Health Organization's (WHO) resolution to incorporate oral cancer into national cancer control programs (Petersen 2009). Although it is important to continue to clarify the public health message and promote primary prevention, determining the feasibility of a national screening programme is an important step in the prevention of the disease. The National Screening Committee define screening as "a process of identifying apparently healthy people who may be at increased risk of a disease or condition" (NSC 2010). Screening can be undertaken across the whole population, opportunistically, when individuals are attending for some other purpose, or selectively, where high-risk groups are targeted. Programmes for major cancers, such as breast, cervical and bowel cancer have effectively improved the mortality rates and helped to decrease the incidence of these cancers (Gøtzsche 2006; Hewitson 2007). However, it is important to consider both the harms and benefits of any screening programmes. For example, screening for breast cancer has recently been associated with over-diagnosis and unnecessary treatment causing further physical and psychological harms (Gøtzsche 2013) and so any future programme should always balance these considerations.

How the intervention might work

Screening is predicated on the idea that malignancy is preceded by clinically evident lesions, which if identified early and removed, can either prevent their malignant transformation or reduce their staging. The majority of oral carcinomas are preceded by visible lesions, known as potentially malignant disorders (PMDs) (Warnakulasuriya 2007; van der Waal 2009) that exhibit oral epithelial dysplasia (Scully 2009). A visual screen is not surgically invasive, is painless and has been found to be socially acceptable. Additional Table 1 highlights the different types of PMDs that were considered by the WHO's Working Party on Oral Cancer and Precancer to be important (Warnakulasuriya 2007). The most common form of PMD is leukoplakia (Napier 2008), which has an estimated global prevalence of 2.6% (95% confidence interval (CI) 1.72% to 2.74%) (Petti 2003). However, the extent and rate of progression of dysplasia in leukoplakia is not uniform and can vary from site to site and within the same lesion (Napier 2008).

Table 1. Important potentially malignant disorders (PMDs)

The following were identified as PMDs by the World Health Organization's Working Group on Oral Cancer (Warnakulasuriya 2007).

  • Leukoplakia.

  • Erythroplakia.

  • Palatal lesion of reverse cigar smoking.

  • Oral lichen planus.

  • Oral submucous fibrosis.

  • Discoid lupus erythematosus.

  • Hereditary disorders such as dyskeratosis congenita and epidermolysis bullosa.

The overall malignant transformation rate for oral leukoplakia is up to 5% (Scully 2009; van der Waal 2009), but the lack of uniformity in the extent and the rate of dysplastic change in PMDs means that predicting malignant transformation is problematic. However, there remains a consensus in the literature that the majority of cancers are preceded by a detectable pre-clinical phase (Napier 2008).

Although there have been no randomised controlled trials (RCTs) in any developed or low-prevalence populations (Brocklehurst 2010a), Speight et al demonstrated using a simulated model that an oral examination of high-risk individuals may be a cost-effective screening strategy (Speight 2006). A recent diagnostic test accuracy review looking at the accuracy of conventional oral examination as a screening test in primary settings found sensitivity estimates to range from 0.50 (95% CI 0.07 to 0.93) to 0.99 (95% CI 0.97 to 1.00) with specificity estimates 0.98 (95% CI 0.92 to 1.00) to 0.99 (95% CI 0.99 to 0.99) (Walsh 2013). Positive predictive values ranged from 0.31 to 0.86; negative predictive values ranged from 0.96 to 0.99 (Walsh 2013). Other adjunctive and diagnostic aids can be grouped into visual staining (toluidine blue), oral cytology using brush biopsy and a number of light-based techniques (e.g. ViziLite (Zila Pharmaceuticals, AZ, USA) and VELscope (LED Dental Inc, BC, Canada)) (Brocklehurst 2010a).

Why it is important to do this review

The RCT provides the strongest level of evidence on which to base clinical decisions (Clarkson 2003) and so represents a level of rigor that is appropriate for assessing the effectiveness of any intervention or programme. As with other cancers, screening for oral cancer and PMDs has potential advantages and disadvantages (Speight 1992). Screening and treatment may offer the opportunity to reduce the incidence of invasive lesions and also could help in decreasing the mortality rates associated with oral cancer. Speight et al demonstrated that targeting high risk groups could result in a pronounced increase in the Quality Adjusted Life Years saved and any associated stage shifts could produce significant cost savings (Speight 2006). However, screening also has the potential to generate false positives and false negatives (Wilson 1968). Earlier versions of this Cochrane review concluded that there was insufficient evidence to support or refute the use of screening for oral cancer in the general population (Kujan 2003; Kujan 2006; Brocklehurst 2010c). The purpose of this latest update was to determine whether the evidence base had changed.

Objectives

To assess the effectiveness of current screening methods in decreasing oral cancer mortality.

Methods

Criteria for considering studies for this review

Types of studies

Randomised controlled trials (RCTs) of screening programmes for the early detection of oral cancer or potentially malignant disorder (PMD), which report on the associated mortality rates subsequent to the screen.

Types of participants

Participants involved in population, selective (high-risk) or opportunistic screening programmes were included.

Types of interventions

Any health technology used in a screening programme for the detection of oral cancer or PMD:

  • visual screening;

  • visual staining using toluidine blue;

  • oral cytology using brush biopsies;

  • fluorescence imaging and light-based techniques.

As this was not a diagnostic test accuracy review, the definition of a positive case in each of these categories was not defined; each study was assessed on an individual study-by-study basis.

Types of outcome measures

The primary outcome measure for this review was oral cancer mortality.

Other outcomes included were:

  • incidence of oral cancer or PMD;

  • stage at diagnosis;

  • adverse effects (outcomes from false positive or false negative results, if known);

  • cost data (where reported).

Search methods for identification of studies

Electronic searches

For the identification of studies included or considered for this review, detailed search strategies were developed for each database searched. These were based on the search strategy developed for MEDLINE (OVID) but revised appropriately for each database (Appendix 1). The search strategies for MEDLINE and CANCERLIT used a combination of controlled vocabulary and free text terms. They were linked with the Cochrane Highly Sensitive Search Strategies (CHSSS) for identifying RCTs in MEDLINE: sensitivity maximising versions (2008 revision) as referenced in Chapter 6.4.11.1 and detailed in boxes 6.4.a and 6.4.c of the Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 (updated March 2011) (Higgins 2011). The search of EMBASE was linked to the Cochrane Oral Health Group filter for identifying RCTs.

Databases searched

We searched the following electronic databases.

  • The Cochrane Oral Health Group's Trials Register (to 22 July 2013) (Appendix 2).

  • CENTRAL (The Cochrane Library 2013, Issue 6) (Appendix 3).

  • MEDLINE via OVID (1946 to 22 July 2013) (Appendix 1).

  • EMBASE via OVID (1980 to 22 July 2013) (Appendix 4).

  • CANCERLIT via PubMed (1950 to 22 July 2013) (Appendix 5).

Searching other resources

The following journals were handsearched for this review to 2010:

  • Oral Oncology

  • British Dental Journal

  • Cancer

  • Cancer Research

  • Community Dental Health

  • Community Dentistry and Oral Epidemiology.

For this update, only handsearching done as part of the Cochrane Worldwide Handsearching Programme and uploaded to CENTRAL was included. See the Cochrane Masterlist of handsearched journals for information on journals and issues searched to date.

Language

There were no non-English papers that required translation. Had such trials been identified they would have been translated through The Cochrane Collaboration.

Unpublished trials

The bibliographies of included papers and relevant review articles were checked for studies not identified by the search strategies above. The authors of identified and included studies were also contacted to identify unpublished or ongoing trials.

Data collection and analysis

Selection of studies

The titles and abstracts obtained from initial electronic searches were scanned for relevance independently by two of the review authors (Paul Brocklehurst (PRB), Anne-Marie Glenny (AMG)). Reports from the studies that fulfilled the inclusion criteria were obtained. When there was insufficient data in the study title to determine whether a study fulfilled the inclusion criteria, the full report was obtained and assessed independently by the same review authors. Disagreement was resolved by discussion.

Data extraction and management

All studies meeting the inclusion criteria underwent data extraction and an assessment of risk of bias was made. Studies rejected at this and subsequent stages were recorded in the table of excluded studies. Data from each included study was extracted independently using the tool developed and reported in Kujan 2005. Differences were again resolved by discussion. If a single publication reported two or more separate studies, then each study was extracted separately. If the findings of a single study were spread across two or more publications, then the publications were extracted as one. For each study with more than one control or comparison group for the intervention, the results were extracted for each intervention arm. For each trial the following data were recorded.

  • Year of publication, country of origin and source of study funding.

  • Details of the participants including demographic characteristics and criteria for inclusion.

  • Details on the type of intervention and comparisons.

  • Details on the study design.

  • Details on the outcomes reported, including method of assessment.

Assessment of risk of bias in included studies

Assessment of risk of bias was conducted by three review authors (PRB, AMG, Lucy O'Malley (LO)) using the Cochrane risk of bias assessment tool. The domains that were assessed for each included study were: sequence generation, allocation concealment, blinding, completeness of outcome data, risk of selective outcome reporting and risk of other potential sources of bias.

A description of the domains was tabulated for each included trial, along with a judgement of the risk of bias in accordance with the Cochrane Handbook for Systematic Reviews of Interventions 5.1.0 (Higgins 2011). A summary assessment of the risk of bias across all the domains for each study was then undertaken (Higgins 2011).

  • Low risk of bias - a low risk of bias for all key domains.

  • Unclear risk of bias - an unclear risk of bias for one or more key domains.

  • High risk of bias - a high risk of bias for one or more key domains.

Measures of treatment effect

For dichotomous outcomes, the estimate of effect was expressed as risk ratios with 95% confidence intervals; for continuous outcomes, mean differences were used with 95% confidence intervals.

Unit of analysis issues

The analysis for cluster randomised trials was undertaken, when feasible, at the same level of randomisation, or at an individual level with the effect of clustering being accounted for.

Assessment of heterogeneity

The significance of any discrepancies in the estimates of the treatment effects from the different trials was assessed by means of Cochran's test for heterogeneity, considered statistically significant at the level of P value < 0.1 (Higgins 2011). The percentage total variation across the included studies was used to quantify heterogeneity and expressed as I2, with a value over 50% representing substantial heterogeneity (Higgins 2011).

Assessment of reporting biases

Publication bias would have also been assessed using funnel plot asymmetry (Higgins 2011).

Data synthesis

Meta-analyses would have been undertaken if the number of trials had exceeded a minimum of three. Risk ratios would have been combined for dichotomous data, and mean differences for continuous data using a random-effects model, if data had allowed.

Results

Description of studies

A total of 3239 citations were identified through the MEDLINE searches. The full text of 30 articles were retrieved. Following further screening, 26 of these were excluded with reasons (Characteristics of excluded studies). One of the excluded studies did undertake a community-based randomised controlled trial to examine the efficacy of toluidine blue in Taiwan (Su 2010). However, the primary aim was to determine whether toluidine blue enhanced the detection rate for potentially malignant disorders (PMD), not mortality rate. Although they did link the examined cohort with the National Cancer Registry to determine five-year follow-up, the power calculation was based on the former not the latter. As a result, the study was excluded from this review but included in an accompanying diagnostic test accuracy review (Walsh 2013). Only one study (four reports) met the inclusion criteria (Sankaranarayanan 2000). The principal investigator of the included trial (Dr Sankaranarayanan) was also contacted and no other relevant trials were identified (Figure 1).

Figure 1.

Study flow diagram.

The included study (Trivandrum Oral Cancer Screening Study; Sankaranarayanan 2000) was designed to have an 80% power at the 5% significance level to detect a 35% reduction in the cumulative mortality rate of oral cancer in 12 years of enrolment between the intervention and the control groups. The study commenced in October 1995 and three rounds of screening at three-year intervals were planned for the study. The first round was completed in May 1998 and the second was completed in June 2002. The third round was completed in October 2004. A final round of screening was completed in 2009.

All participants (n = 191,873) were apparently healthy residents aged 35 years or older and lived in 13 rural clusters around Trivandrum City, Kerala, India, The mean number of eligible participants in each cluster was 14,759. These clusters were allocated into an intervention arm (n = 7) and a control arm (n = 6) by a blocked randomisation process. Those residents who were bedridden, suffering from open tuberculosis or other debilitating diseases were excluded alongside those participants who had already been diagnosed with oral cancer prior to entry into the study.

In the intervention arm, non-medical university graduates were initially trained and were provided with two simple manuals on oral visual examination with colour photographs and descriptions of various oral lesions. Eligible participants were interviewed and information relating to demographic, social and personal habits including the use of paan, tobacco, alcohol and dietary supplements was recorded. Tobacco and alcohol cessation advice was provided as appropriate. Oral visual inspections were performed in daylight with the help of a flashlight. All the intra-oral sites were carefully examined and palpated and the neck was also palpated to detect enlarged lymph nodes. The findings were recorded as normal, non-referable lesions and referable lesions.

Participants who had a positive screen were referred for examination by a dentist or physician for confirmation. It is unclear whether these clinicians were also trained in the recognition of oral cancer or PMDs. Oral biopsies were performed in those with clinically confirmed homogeneous leukoplakias, non-homogeneous leukoplakias, oral submucous fibrosis and oral cancers. Surgical excision was undertaken for leukoplakia wherever possible. All PMDs were reviewed regularly.

In the control arm, participants were visited by a "control health worker" who recorded the same sociodemographic information and measured height, weight, blood pressure and respiratory peak flow measurements. The health workers in the control arm were not trained to undertake a visual oral inspection.

Oral cancer mortality was reported as the main outcome measure.

Of the 96,517 eligible subjects in the intervention arm, 25,144 (26.1%) had one, 22,382 (23.2%) had two, 22,008 (22.8%) had three and 19,288 (20.0%) had four cycles of screening. 49,179 (51.0%) individuals were screened in the first round and 55,993 (58.0%), 64,898 (67.2%) and 43,014 (44.6%) were screened in the second, third and fourth cycles respectively. The participation rate (at least one screen) for this group was 88,822 (92%); males (86%) and females (94%). Of the 95,356 eligible subjects in the control group, 43,992 (46.1%) were screened in the fourth cycle.

Demographic details were not provided for the final (fourth) cycle of screening, but were provided for the first three cycles (Additional Table 2). Across the period of the study (all four cycles), 6.3% (n = 5586) of subjects screened as part of the intervention group had a referable lesion and 59% (n = 3298) of these screen positive subjects complied with referral (Additional Table 3). The control group consisted of 95,356 persons. 46% (n = 43,992) of the control group were screened in the final (fourth) cycle and 2.6% (n = 1163) of these were found to have a referable lesion with 16.3% (n = 189) complying with referral.

Table 2. Comparison of risk factors between the intervention and control groups after three cycles (nine years) follow-up
  1. SD = standard deviation.
    Note: Data on risk factors not available after 4 cycles (15 years), but authors report that the participants had a similar distribution.

Trivandrum Oral Cancer Screening StudyScreening groupControl group
Number of interviewed participantsn = 7 clusters (87,829: 91%)n = 6 clusters (80,086: 84%)
Gender

35,687 male

52,142 female

31,281 male

48,805 female

Income (< 1500 rupees (USD 35) per month)42,415 (49%)30,849 (40%)
Occupation (manual workers)68,645 (78%)55,811 (71%)
Education68,263 (78%)64,291 (78%)
Age (years; mean (SD, range))49 (0.7, 48-50)49 (0.8, 48-50)
No habits

10,933 male (27%)

39,923 female (73%)

13,996 male (33%)

42,361 female (79%)

Chewing habits

12,329 male (30%)

14,570 female (27%)

10,586 male (24.9%)

10,748 female (20%)

Smoking habits

26,133 male (63%)

1610 female (3%)

23,270 male (56%)

609 female (1%)

Drinking habits

17,738 male (43%)

133 female (0.2%)

15,472 male (37%)

127 female (0.1%)

Table 3. Screening history after four cycles (15 years) follow-up
Screening historyScreening groupControl
Number recruited

7 clusters

(n = 96,517)

6 clusters

(n = 95,356)

Not screened769551,365
Screened once25,14443,992
Screened twice22,382 
Screened three times22,008 
Screened four times19,288 
Number of screen positive individuals55861163
Individuals complied with referral3298189

Risk of bias in included studies

Allocation

Sequence generation

The randomisation procedure was conducted using restricted block randomisation. The exact detail of this process was not provided, although the clusters were grouped into blocks of four and allocated at random to screening or non-screening groups from the six possible combinations available to each block of four. Clustering was not accounted for in the analysis.

Allocation concealment

No detail of allocation concealment was provided, although the principal investigator confirmed that this was not undertaken.

Blinding

Blinding of outcome assessment

No blinding was undertaken in the study, but the review authors judge that the outcome and its measurement are unlikely to be influenced by this. As a result, the risk of bias based on the lack of blinding is considered to be low.

Incomplete outcome data

Withdrawals and drop-outs were not described clearly and missing data will have increased the risk of bias. Of those who were referred with positive lesions, 59% of individuals in the screening group complied with referral and 16% in the control group (Additional Table 3). The analysis was carried out on an intention-to-treat (ITT) basis.

Selective reporting

The study protocol was not made available, but it appears that the published reports include all the expected and pre-specified outcome measures.

Other potential sources of bias

Positive cases were referred to dentists and physicians to make a diagnosis, but it is unclear whether standardised criteria were used by these clinicians or whether they had received any formal training. It is stated that subjects with confirmed oral cancer and PMDs were biopsied and those with confirmed oral cancer were referred. However, this detail was absent and only 26.4% and 26.0% of subjects with a PMD had a biopsy in the second or third cycle respectively. It is not clear whether all suspected oral cancer cases did receive a biopsy, but given the definition of "interval cases" in the third paper, it would appear not.

In addition, it is stated in the third paper that the reference investigation for final diagnosis was clinical examination by physicians or histology or both. As it is not possible to diagnose early malignancy by visual appearance alone, this may have led to substantial under-reporting of oral cancer. The lack of a histological diagnosis for many of the PMDs also makes it difficult to accurately assess the correct diagnosis and true prevalence of these disorders. Prevalence of PMDs is provided in detail for the first two cycles only. The fourth paper presents incidence and mortality data for each round of screening. Neither the third or fourth papers present data regarding prevalence of PMDs.

In the included study the health workers reported on 24 baseline variables including multiple age strata, occupation, education, income, household belongings such as television and personal habits of chewing, smoking, and drinking. The intervention and control cohorts appear to have been well matched for the stratified variable age at the baseline. However, the distribution of income, education, use of tobacco and alcohol varied across the intervention and control groups, with the former demonstrating higher levels of consumption (Additional Table 2). Men smoked and drank alcohol more than females in both groups, but the prevalence of chewing tobacco was not as marked across gender differences. Although, such differences in baseline variables might be expected to occur in cluster randomised studies, the differences between the numbers who used tobacco and alcohol need to be borne in mind when interpreting the results.

Effects of interventions

The included study reported data on oral cancer incidence, disease-specific mortality, and stage at diagnosis after 15-years follow-up. Data on quality of life and all cause mortality were not reported.

Oral cancer mortality

There was a 12% reduction in oral cancer mortality between the intervention and control arms, but this difference was not statistically significant. Over the four cycles (15 years), 138 of 279 subjects with oral cancer in the intervention group and 154 of the 244 cases in the control group died, which represents a mortality rate of 15.4 and 17.1 per 100,000 person-years respectively (risk ratio (RR) 0.88; 95% confidence interval (CI) 0.69 to 1.12). Age-adjusted rates were 18.9 per 100,000 person-years in the intervention group and 19.7 per 100,000 person-years in the control (Additional Table 4).

Table 4. Oral cancer experience after four cycles (15 years) follow-up
  1. 1Does not include individuals for whom stage unknown (22 in screening group; 19 in control group).

Trivandrum Oral Cancer Screening StudyScreening groupControl groupRisk ratio (95% confidence interval)
Total number participants96,51795,356 
Person-years of observation895,310898,280 
Number of oral cancers279244 
Screen detected cases188Nil 
Deaths from oral cancer138154 
Case fatality rate49.5%63.1% 
Crude incidence rate / 100,000 person-years of observation31.227.21.14 (0.91 to 1.44)
Age-standardised incidence rate / 100,000 person-years37.130.8 
Crude mortality rate from oral cancer /100,000 person-years of observation15.417.10.88 (0.69 to 1.12)
Age-standardised mortality rate / 100,000 person-years18.919.7 
Proportion of cancers at stage III or worse152.6%65.2%0.81 (0.70 to 0.93)

There was a 24% reduction in oral cancer mortality between the intervention and control arms for those participants who used tobacco or alcohol or both and this difference was statistically significant. Over the four cycles (15 years), 129 of 254 subjects with oral cancer in the intervention group and 147 of the 232 cases in the control group died, which represents a mortality rate of 30.0 and 39.0 per 100,000 person-years respectively (RR 0.76; 95% CI 0.60 to 0.97) (Additional Table 5). Age-adjusted rates were 29.1 per 100,000 person-years in the intervention group and 37.1 per 100,000 person-years in the control (Additional Table 4).

Table 5. Oral cancer experience in high-risk individuals after four cycles (15 years) follow-up
  1. 1Does not include individuals for whom stage unknown (22 in screening group; 19 in control group).

Trivandrum Oral Cancer Screening StudyScreening groupControl groupRisk ratio (95% confidence interval)
Person-years of observation429,620377,350 
Number of oral cancer cases254232 
Deaths from oral cancer129147 
Case fatality rate50.8%63.4% 
Crude incidence rate/ 100,000 person-years59.261.60.97 (0.79 to 1.19)
Age-standardised incidence rate/ 100,000 person-years57.358.5 
Crude mortality rate/ 100,000 person-years30.039.00.76 (0.60 to 0.97)
Age-standardised mortality rate/ 100,000 person-years29.137.1 
Age-standardised mortality rate/ 100,000 person-years18.919.7 
Proportion of cancers at stage III or worse154.3%66.4%0.82 (0.71 to 0.95)

Although data presented after four cycles (15 years) were not divided by gender, the three-year cycle data (nine years) showed a significant reduction of 43% in mortality rates for men from 42.9 per 100,000 person-years in the control group to 24.6 per 100,000 person-years in the intervention group. For women, there was a 22% reduction, from 50.7 to 39.4 per 100,000 person-years, but this did not reach significance.

For the participants that adhered to all four cycles of the screening programme, there was a 79% reduction in oral cancer mortality (81% amongst the users of tobacco or alcohol or both) compared to the control, which was statistically significant (Additional Table 6).

Table 6. Oral cancer mortality rate by number of times screened
  1. *Per 100,000 person-years of observation

    **Adjusted for age, sex and number of residents.

Risk typeArmCyclesMortality rate*Hazard ratio (95% confidence interval)**
All participants Controln/a17.11.00
Screening group037.21.46 (0.78 to 2.73)
144.12.26 (1.66 to 3.09)
216.20.94 (0.68 to 1.30)
310.40.62 (0.37 to 1.04)
43.00.21 (0.13 to 0.35)
High-risk participants Controln/a39.01.00
Screening group059.41.27 (0.68 to 2.37)
174.71.90 (1.45 to 2.49)
231.00.83 (0.62 to 1.12)
320.60.53 (0.34 to 0.84)
47.10.19 (0.11 to 0.31)

Oral cancer incidence

Among the 96,517 participants screened in the intervention group, 5586 (6.3%) were found to have referable lesions. Of these, 3298 (59%) complied with the referral criteria for confirmatory examination by dentists or medical officers in special clinics. Healthy mucosa or benign lesions were found in 770 (23.3%). The number of PMDs was 2336 (70.8%) (lichen planus (n = 53), homogenous leukoplakia (n = 898) and submucous fibrosis (n = 573)) and growths suspicious of oral cancer 192/3298 (4%). Of those diagnosed with PMDs, 21.4% (n = 499), underwent biopsies and 4.4% (n = 22) were confirmed squamous cell carcinoma. Of those diagnosed with suspicious growths, 84.9% (n = 163) were confirmed as squamous cell carcinoma and 1.6% (n = 3) as verrucous carcinoma.

The detection rate of PMD and oral cancer in the first, second, and third and fourth rounds of screening were 28.0, 11.9, 11.6 and 3.9 per 1000 screened subjects respectively. The crude incident rate of oral cancer was 31.2 per 100,000 person-years in the screening group and 27.2 per 100,000 person-years in the control group, with a risk ratio of 1.14 (95% CI 0.91 to 1.44). Age-adjusted incidence rates were 37.1 per 100,000 person-years and 30.8 per 100,000 person-years respectively (Additional Table 4).

Test performance

Across the four cycles (15 years) of the programme, the reported sensitivity of the visual examination in detecting oral cancer was 67.4% (188/279) (Additional Table 4). No information on the specificity or the positive predictive value of the programme was recorded.

Survival

Survival rates were calculated by comparing the proportion of patients alive at five years after diagnosis across the two groups. A significantly higher five-year survival rate was reported in the screened group (55.5%) compared to the control (43.4%) (P value = 0.003).

Stage shift at diagnosis

There was a statistically significant stage shift in the cancers that were diagnosed in the screened group, based on the criteria of the International Union Against Cancer/American Joint Committee on Cancer (UICC/AJCC). In the screened group, 147/279 (52.6%) cases were in stage III or worse at diagnosis, as opposed to 159/244 (65.2%) of cases in the control group (RR 0.81; 95% CI 0.70 to 0.93) (Additional Table 4; Additional Table 7). For users of tobacco, alcohol or both, 138/254 (54.3%) cases were in stage III or worse at diagnosis in the screened group, as opposed to 154/232 (66.4%) of cases in the control group (RR 0.82; 95% CI 0.71 to 0.95) (Additional Table 5; Additional Table 7).

Table 7. Distribution of stage over four cycles (15 years)
ArmCyclesClinical stageTotal
I II III IV Unknown
Intervention groupBaseline03 (16%)3 (16%)7 (37%)6 (32%)19
19 (11%)10 (13%)18 (23%)32 (41%)10 (13%)79
210 (15%)11 (17%)17 (26%)25 (38%)3 (5%)66
323 (32%)12 (17%)9 (13%)25 (35%)3 (4%)72
417 (40%)15 (35%)4 (9%)7 (34%)043
Total 59 (21%) 51 (18%) 51 (18%) 96 (34%) 22 (8%) 279
Control group1996 - 2004 (detected not due to screening)21 (13%)19 (12%)34 (22%)72 (46%)12 (8%)158
Not screened07 (16%)12 (27%)20 (44%)6 (13%)45
Screened10 (24%)9 (22%)6 (15%)15 (37%)1 (2%)41
Total 31 (13%) 35 (14%) 52 (21%) 107 (44%) 19 (8%) 244

Cost-effectiveness

The costs associated with the screening programme were reported after three cycles (nine years) (Subramanian 2009) (Additional Table 8). The benefit produced by a screen was 269.31 life-years saved per 100,000 for all the individuals and 1437.64 for those at high risk. The incremental cost per life-year saved was USD 835 for all individuals, which reduced to USD 156 for high-risk individuals. This fulfils the target set by the World Health Organization (WHO) Commission on Macroeconomics and Health (WHO 2001), who define an intervention to be cost-effective when its cost-effectiveness ratio is less than a country's gross domestic product per capita. Subramanian argues that this provides good evidence that opportunistic screening of high-risk groups is cost-effective (Subramanian 2009).

Table 8. Cost-effectiveness of the screening programme after three cycles (nine years)
  1. Costs based on the calender year of 2004 (Subramanian 2009).

Detail Cost of intervention less cost of control (US$)
Total cost per 100,000 individuals224,964
Cost per additional cancer detected by the screenAll individuals4817
Cost per additional cancer detected by the screenHigh-risk individuals9394
Cost per life-year saved by the screenAll individuals835
Cost per life-year saved by the screenHigh-risk individuals156

Discussion

The incidence of oral cancer is increasing in low, middle and high-income countries (Warnakulasuriya 2009). Delays in diagnosis and management persist (Onizawa 2003; McLeod 2005) and are associated with a dramatic deterioration in five-year survival rates. Effective primary and secondary prevention strategies are critical in delivering the World Health Organization's (WHO) resolution that oral cancer should be an integral part of national cancer control programmes (Petersen 2009).

Given that the majority of oral carcinomas are preceded by visible lesions (Scully 2009), determining the efficacy and effectiveness of screening warrants attention, whilst balancing the potential benefits with any potential negative consequences of any programme (Wilson 1968).

Summary of main results

The study reported a sensitivity of the visual examination in detecting oral cancer was 67.4%. However, the data for users of tobacco, alcohol or both demonstrated a reduction in mortality rates of 24% after four cycles (15 years), which was statistically significant. In addition, there was a statistically significant difference in the number of stage III cancers between the intervention and control arms, suggesting that the screening programme was identifying cancers at an early stage. When these results are combined with the significant stage shift and survival rate in the intervention group, it would appear that visual examination could be effective at reducing mortality rates for oral cancer when used within a targeted screening programme. However, the included study had a high risk of bias.

Overall completeness and applicability of evidence

The purpose of health care is to improve both the quantity and quality of life (Kaplan 2005). The evidence from the Kerala trial (Sankaranarayanan 2000) is that visual screening can reduce the mortality rate in users of tobacco, alcohol or both and can produce a stage shift. Given that late stage disease is recognised as a major contributory factor for cancer survival (Onizawa 2003; McLeod 2005), it would appear that the screening of high-risk individuals could be warranted. However, the evidence from this study stems from a population with a high incidence of oral cavity cancer, and its applicability to other countries with lower incidence rates is unknown. In addition, the efficacy of the early management of potentially malignant disorders (PMDs) is a controversial area (Holmstrup 2007; Holmstrup 2009). Holmstrup argues that even if early lesions are surgically removed, the risk of malignant change can remain as a result of "field change" i.e. the lesion represents only a small area of a wider field of damaged mucosa (Holmstrup 2007; Holmstrup 2009).

The trial used non-medical university graduates, trained specifically to perform visual inspection of the oral mucosa, with the help of a flashlight. The screening was undertaken in individuals own home, with the health workers going 'door-to-door'. The ability to translate this screening model to other settings is unclear. However, the Kerala study does demonstrate the potential of allied health professionals to screen for oral cancer and PMDs. This is becoming increasingly relevant as more regulators allow patients to directly access allied providers of dental care (oral health practitioners), in addition to the dentist.

The cost-effectiveness of the Kerala study was reported after three cycles (nine years) (Subramanian 2009), demonstrating that 1437.64 life-years could be saved per 100,000 high-risk individuals, with an incremental cost per life-year saved of USD 156. According to the authors, this fulfils the target set by the WHO Commission on Macroeconomics and Health, who define an intervention as being cost-effective when its cost-effectiveness ratio is less than a country's gross domestic product per capita. However, these results also need to be read in context of the relative prevalence of the condition and account for the potential problem of compliance; out of the 5586 participants that were screened positive, only 59% (n = 3298) complied with referral.

The consideration of both the benefits and harms of screening is an essential component of any programme (Wilson 1968) and is fundamental to the satisfactory introduction of any technology into daily practice (Duffy 2001). The sensitivity reported in the Kerala study was relatively low (67%). In addition, false positives can have unintended psychological consequences, for example, increasing anxiety and exposing the patient to unnecessary further investigations. However, these could be reduced by careful patient management and by educating screened patients about the positive benefits of screening (Speight 1992). Recent studies by Brocklehurst, highlighted the need to train general dental practitioners to discuss positive findings (Brocklehurst 2010b) and the need for standardised criteria to avoid both under and over-referral in clinical practice (Brocklehurst 2010).

Quality of the evidence

The Kerala study had a number of methodological weaknesses that may have introduced bias. These included a lack of detail about the process of sequence generation to ensure random assignment, no analysis of the impact of clustering on the results and no detail about allocation concealment. In addition, there was no blinding of the outcome assessment and withdrawals and drop-outs were not described. More importantly, only 59% of individuals with screen-positive lesions in the intervention arm complied with referral and it was unclear whether the clinicians who saw these patients followed any standardised criteria. In addition, only 26.4%, 26.0%, and 21.4% of subjects had a biopsy in the second, third cycle or fourth cycle respectively, with no detail being provided from the first cycle. As it is not possible to diagnose early malignancy by visual appearance alone, this may have led to substantial under-reporting of oral cancer and the lack of a histological diagnosis makes it difficult to accurately assess the correct diagnosis and true prevalence of these disorders. It has been argued that the small number of randomised clusters could also produce statistical heterogeneity and the close geographical proximity of the clusters may have led to contamination (Kujan 2005).

Potential biases in the review process

We conducted a broad search of several databases and placed no restrictions on the language of publication when searching the electronic databases or reviewing reference lists of included studies. All data extraction and risk of bias assessment was conducted in duplicate.

Agreements and disagreements with other studies or reviews

A meta-analysis of visual screening found a weighted and pooled sensitivity of 84.8% (95% confidence interval (CI) 73.0 to 91.9) and specificity of 96.5% (95% CI 93.0 to 98.2) (Downer 2004). However, there was considerable heterogeneity in the studies pooled due to differences in the size of the target populations and it is arguable that a meta-analysis was inappropriate. A more recent review has evaluated the diagnostic accuracy of non-specialist conventional oral examination, vital rinsing, light-based detection, biomarkers and mouth self examination for the identification of individuals with suspected oral squamous cell carcinoma or PMD. Sensitivity values for studies for all tests were varied and relatively imprecise with sensitivity values ranging from 0.59 (0.39 to 0.78) to 0.99 (95% CI 0.97 to 1.00) for the conventional oral examination (Walsh 2013).

These values of sensitivity and specificity for visual examination have not been surpassed by any other type of method, such as self examination, vital staining (toluidine blue), oral cytology or light-based techniques (Lingen 2008; Patton 2008; Walsh 2013). The review by Walsh et al showed sensitivity values ranging from 0.18 (95% CI 0.13 to 0.24) to 0.33 (95% CI 0.10 to 0.65) for mouth self examination and a sensitivity value of 0.20 (95% 0.01 to 0.72) for the addition of toluidine blue (Walsh 2013). In Patton's systematic review, 23 studies met the inclusion criteria, yet there remained insufficient evidence to support or refute the use of adjunctive techniques to the visual examination (Patton 2008). In another review, Lingen found that the majority of the published studies had employed these techniques on patients who had already received a diagnosis and that they did not improve upon the sensitivity or specificity of the visual examination (Lingen 2008).

Authors' conclusions

Implications for practice

The results suggest that there is insufficient evidence to recommend a whole population screening programme for oral cancer. However, the results from the Kerala study suggest that a targeted population approach could reduce the mortality rate and produce a stage shift, but the risk of bias in the included study means that further well-designed randomised controlled trials are necessary to establish the validity of this relationship.

In the meantime, opportunistic visual screening by appropriately trained dentists and oral health practitioners is recommended for all patients and particularly for those who use tobacco, alcohol or both. Systematic examination of the oral cavity by front-line health workers should remain an integral part of their routine for routine recall appointments.

Implications for research

Given the high risk of bias in the study included in this review, a lack of randomised controlled studies associated with adjunctive methods (e.g. brush biopsy, fluorescence imaging) and a lack of understanding of the natural history of oral cancer, further randomised controlled trials are recommended. These should ensure the method of randomisation is accounted for in the analysis, that there is adequate allocation concealment, a standardised intervention and a clear follow-up procedure.

Acknowledgements

We would like to thank Dr Sankaranarayanan for answering the queries of the review group. We would also like to thank Anne Littlewood (Cochrane Oral Health Group) for her help with preparing the searches for this update. We are also grateful to Professor Helen Worthington for her assistance on the development of the initial review and the Editors at the Cochrane Oral Health Group for their valuable comments.

Data and analyses

Download statistical data

This review has no analyses.

Appendices

Appendix 1. MEDLINE via OVID search strategy

1. exp MOUTH/
2. exp LIP/
3. exp GINGIVA/
4. exp TONGUE/
5. exp OROPHARYNX/
6. exp HYPOPHARYNX/
7. exp PALATE/
8. exp CHEEK/
9. (mouth or lip$ or tongue$ or gingiv$ or oropharynx or palate or cheek$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
10. or/1-9
11. exp MOUTH NEOPLASMS/
12. exp PRECANCEROUS CONDITIONS/
13. (tumor$ or tumour$ or cancer$ or carcinoma$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
14. malignan$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
15. dysplasia$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
16. (oral adj6 cancer$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
17. or/11-16
18. MASS SCREENING/
19. (visual$ adj screen$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
20. tolonium chloride.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
21. TOLONIUM CHLORIDE/
22. "toluidine blue".mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
23. exp TOLUIDINES/
24. "toluidine dye".mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
25. ("brush biopsy" or "exfoliate cytology").mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
26. "fluorescent imaging".mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
27. ("fluorescent dye$" or "fluorescent antibody technique" or fluorescence).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
28. prevent$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
29. screen$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
30. (early adj3 detect$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
31. or/18-30
32. 10 and 17 and 31

The above subject search was linked to the the Cochrane Highly Sensitive Search Strategy (CHSSS) for identifying randomised trials in MEDLINE: sensitivity maximising version (2008 revision) as referenced in Chapter 6.4.11.1 and detailed in box 6.4.c of theCochrane Handbook for Systematic Reviews of Interventions, Version 5.1.0 (updated March 2011).

1. randomized controlled trial.pt.
2. controlled clinical trial.pt.
3. randomized.ab.
4. placebo.ab.
5. drug therapy.fs.
6. randomly.ab.
7. trial.ab.
8. groups.ab.
9. or/1-8
10. exp animals/ not humans.sh.
11. 9 not 10

Appendix 2. Cochrane Oral Health Group's Trials Register search strategy

From 2013, searches of the Cochrane Oral Health Group's Trials Register were updated using the Cochrane Register of Studies software and the search strategy below:

#1 (tumor* or tumour* or cancer* or carcinoma* or malignan*):ti,ab
#2 (screen* or tolonium or "brush biopsy" or "exfoliative cytology" or fluorescen* or "early detect*"):ti,ab
#3 #1 and #2

Previous searches of the Oral Health Group's Trials Register were undertaken using the Procite software and the search strategy below:

((tumor* or tumour* or cancer* or carcinoma* or malignan*) AND (screen* or tolonium or "brush biopsy" or "exfoliative cytology" or fluorescen* or "early detect*"))

Appendix 3. Cochrane Central Register of Controlled Trials (CENTRAL) search strategy

#1 MeSH descriptor MOUTH explode all trees
#2 MeSH descriptor LIP explode all trees
#3 MeSH descriptor GINGIVA this term only
#4 MeSH descriptor TONGUE explode all trees
#5 MeSH descriptor OROPHARYNX explode all trees
#6 MeSH descriptor HYPOPHARYNX explode all trees
#7 MeSH descriptor PALATE explode all trees
#8 MeSH descriptor CHEEK this term only
#9 (mouth* in All Text or lip* in All Text or tongue* in All Text or gingiv* in All Text or oropharnyx in All Text or palate* in All Text or cheek* in All Text)
#10 (#1 or #2 or #3 or #4 or #5 or #6 or #7 or #8 or #9)
#11 MeSH descriptor MOUTH NEOPLASMS explode all trees
#12 MeSH descriptor PRECANCEROUS CONDITIONS explode all trees
#13 (tumor* in All Text or tumour* in All Text or cancer* in All Text or carcinoma* in All Text)
#14 malignan* in All Text
#15 dysplasia* in All Text
#16 (oral in All Text near/6 cancer* in All Text)
#17 (#11 or #12 or #13 or #14 or #15 or #16)
#18 MeSH descriptor Mass Screening explode all trees
#19 "visual* screen*" in All Text
#20 "tolonium chloride" in All Text
#21 MeSH descriptor TOLONIUM CHLORIDE this term only
#22 "toluidine blue" in All Text
#23 MeSH descriptor TOLUIDINES explode all trees
#24 "toluidine dye" in All Text
#25 ("brush biopsy" in All Text or "exfoliate cytology" in All Text)
#26 "fluorescent imaging" in All Text
#27 ("fluorescent dye*" in All Text or "fluorescent antibody technique" in All Text or fluorescence in All Text)
#28 prevent* in All Text
#29 screen* in All Text
#30 (early in All Text near/3 detect* in All Text)
#31 (#18 or #19 or #20 or #21 or #22 or #23 or #24 or #25 or #26 or #27 or #28 or #29 or #30)
#32 (#10 and #17 and #31)

Appendix 4. EMBASE via OVID search strategy

1. exp MOUTH/
2. exp LIP/
3. exp GINGIVA/
4. exp TONGUE/
5. exp OROPHARYNX/
6. exp HYPOPHARYNX/
7. exp PALATE/
8. exp CHEEK/
9. (mouth or lip$ or tongue$ or gingiv$ or oropharynx or palate or cheek$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
10. or/1-9
11. exp MOUTH NEOPLASMS/
12. exp PRECANCEROUS CONDITIONS/
13. (tumor$ or tumour$ or cancer$ or carcinoma$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
14. malignan$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
15. dysplasia$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
16. (oral adj6 cancer$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
17. or/11-16
18. MASS SCREENING/
19. (visual$ adj screen$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
20. tolonium chloride.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
21. TOLONIUM CHLORIDE/
22. "toluidine blue".mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
23. exp TOLUIDINES/
24. "toluidine dye".mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
25. ("brush biopsy" or "exfoliate cytology").mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
26. "fluorescent imaging".mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
27. ("fluorescent dye$" or "fluorescent antibody technique" or fluorescence).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
28. prevent$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
29. screen$.mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
30. (early adj3 detect$).mp. [mp=title, original title, abstract, name of substance word, subject heading word, unique identifier]
31. or/18-30
32. 10 and 17 and 31

The above subject search was linked to the Cochrane Oral Health Group filter for identifying RCTs in EMBASE via OVID.

1. random$.ti,ab.
2. factorial$.ti,ab.
3. (crossover$ or cross over$ or cross-over$).ti,ab.
4. placebo$.ti,ab.
5. (doubl$ adj blind$).ti,ab.
6. (singl$ adj blind$).ti,ab.
7. assign$.ti,ab.
8. allocat$.ti,ab.
9. volunteer$.ti,ab.
10. CROSSOVER PROCEDURE.sh.
11. DOUBLE-BLIND PROCEDURE.sh.
12. RANDOMIZED CONTROLLED TRIAL.sh.
13. SINGLE BLIND PROCEDURE.sh.
14. or/1-13
15. (exp animal/ or animal.hw. or nonhuman/) not (exp human/ or human cell/ or (human or humans).ti.)
16. 14 NOT 15

Appendix 5. CANCERLIT via PubMed search strategy

#1 Search MOUTH [mh:exp]
#2 Search LIP [mh:exp]
#3 Search GINGIVA [mh:exp]
#4 Search TONGUE [mh:exp]
#5 Search OROPHARYNX [mh:exp]
#6 Search HYPOPHARYNX [mh:exp]
#7 Search PALATE [mh:exp]
#8 Search CHEEK [mh:exp]
#9 Search (mouth or lip* or tongue* or gingiv* or oropharynx or palate or cheek*)
#10 Search #1 or #2 or #3 pr #4 or #5 or #6 or #7 or #8 or #9
#11 Search MOUTH NEOPLASMS [mh:exp]
#12 Search PRECANCEROUS CONDITIONS [mh:exp]
#13 Search (tumor* or tumour* or cancer* or carcinoma*)
#14 Search malignan*
#15 Search dysplasia*
#16 Search "oral cancer*"
#17 Search #11 or #12 or #13 or #14 or #15 or #16
#18 Search MASS SCREENING [mh:exp]
#19 Search "visual* screen*"
#20 Search "tolonium chloride"
#21 Search TOLONIUM CHLORIDE [mh:noexp]
#22 Search "toluidine blue"
#23 Search TOLUIDINES [mh:exp]
#24 Search "toluidine dye"
#25 Search ("brush biopsy" or "exfoliate cytology")
#26 Search "fluorescent imaging"
#27 Search ("fluorescent dye*" or "fluorescent antibody technique" or fluorescence)
#28 Search prevent*
#29 Search screen*
#30 Search "early detect*"
#31 Search #18 or #19 or #20 or #21 or #22 or #23 or #24 or #25 or #26 or #27 or #28 or #29 or #30

The above subject search was linked to the Cochrane Highly Sensitive Search Strategy (CHSSS) for identifying randomised trials in MEDLINE: sensitivity maximising version (2008 revision) as referenced in Chapter 6.4.11.1 and detailed in box 6.4.a of the Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 (updated March 2011).

#1 randomized controlled trial [pt]
#2 controlled clinical trial [pt]
#3 randomized [tiab]
#4 placebo [tiab]
#5 drug therapy [sh]
#6 randomly [tiab]
#7 trial [tiab]
#8 groups [tiab]
#9 #1 OR #2 OR #3 OR #4 OR #5 OR #6 OR #7 OR #8
#10 animals [mh] NOT humans [mh]
#11 #9 NOT #10

What's new

DateEventDescription
12 September 2013New search has been performedSearches updated on 22 July 2013.
12 September 2013New citation required but conclusions have not changedThis version includes a change in authors. Review text, methodology, background and references brought up to date.

History

Protocol first published: Issue 2, 2003
Review first published: Issue 4, 2003

DateEventDescription
6 October 2010New citation required but conclusions have not changedNew authorship.
6 October 2010New search has been performedNew searches and methodology. Review text, background and references brought up to date.
25 May 2006New citation required but conclusions have not changedThis version includes a change in authors.
23 May 2006New search has been performedThe current review reflects the results of an update search conducted in July 2005. No new trials were identified as meeting the review's inclusion criteria. However, a trial presenting the final analysis for the one, previously included trial was identified. The conclusions of the review remain the same.

Contributions of authors

Development of protocol based on the latest Cochrane guidance: Paul Brocklehurst (PRB).
Identification of studies: PRB, Anne-Marie Glenny (AMG), Lucy O'Malley (LO).
Data extraction: PRB, AMG, LO.
Assessment of risk of bias: PRB, AMG, LO.
Data input/synthesis: PRB, AMG, LO.
Writing of conclusions: PRB, AMG, Omar Kujan (OK), Graham Ogden (GO), Simon Shepherd (SS).

Declarations of interest

Paul Brocklehurst: no interests to declare.
Omar Kujan: no interests to declare.
Lucy A O'Malley: no interests to declare.
Graham Ogden: no interests to declare.
Simon Shepherd: no interests to declare.
Anne-Marie Glenny: no interests to declare.

Sources of support

Internal sources

  • The University of Manchester, UK.

  • AlBaath University, Syrian Arab Republic.

  • Manchester Academic Health Sciences Centre (MAHSC), UK.

    The Cochrane Oral Health Group is supported by MAHSC and the NIHR Manchester Biomedical Research Centre

External sources

  • Cochrane Oral Health Group Global Alliance, UK.

    All reviews in the Cochrane Oral Health Group are supported by Global Alliance member organisations (British Association of Oral Surgeons, UK; British Orthodontic Society, UK; British Society of Paediatric Dentistry, UK; British Society of Periodontology, UK; Canadian Dental Hygienists Association, Canada; National Center for Dental Hygiene Research & Practice, USA; Mayo Clinic, USA; New York University College of Dentistry, USA; and Royal College of Surgeons of Edinburgh, UK) providing funding for the editorial process (http://ohg.cochrane.org/)

  • National Institute for Health Research (NIHR), UK.

    CRG funding acknowledgement:
    The NIHR is the largest single funder of the Cochrane Oral Health Group
    Disclaimer:
    The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the NIHR, NHS or the Department of Health

Characteristics of studies

Characteristics of included studies [ordered by study ID]

Sankaranarayanan 2000

  1. a

    PMDs = potentially malignant disorders.

Methods

Randomised controlled trial, Kerala, India.
First round: 1995 to 1998.
Second round: 1998 to 2002.
Third round: 2002 to 2004.

Final assessment: 2004 to 2009.

ParticipantsGeneral population aged 35 years or older, all subjects 191,873 were apparently healthy residents were grouped into intervention (n = 7 clusters, 96,517) and control (n = 6 clusters, 95,356).
Interventions

Health workers interviewed the eligible subjects to extract specified information. Intervention group: visual examination of the oral mucosa.
Control group: follow-up to the end point.

The intervention and control cohorts are being followed up by the Trivandrum population-based cancer registry to determine the incidence and stage distribution of invasive oral cancer, treatment given and mortality.

OutcomesOral cancer mortality was the major outcome. Further outcome measures were.
1. Participation: defined as "the number of eligible subjects screened as a proportion of the total eligible in the intervention arm".
2. Positivity rate: defined as "the proportion of screened subjects identified with referable lesions".
3. Detection rate: defined as "the number of subjects with lesions detected per 1000 screened subjects in the intervention group".
4. Compliance with referral: defined as "the proportion of screen positive subjects reporting for diagnostic confirmation by dentists or physicians".
5. Sensitivity, specificity, and positive predictive values.
6. Programme sensitivity and specificity: defined as "the number of screen-detected oral cancers as a proportion of the total oral cancers in the intervention group", "the proportion of screen true-negative subjects among the total non-cancer-eligible subjects" and "the number of screen-detected oral cancers as a proportion of total screen positive subjects" respectively.
7. Incidence rate of oral cancers.
8. Characteristics of oral cancers in the study group including: the maximum dimension of lesions, regional lymph node involvement and International Union Against Cancer/American Joint Committee on Cancer (UICC/AJCC) TNM stage grouping distribution.
9. Case fatality for oral cancer cases diagnosed during the study period: defined as "the number of deaths among the total number of cases".
Notes 
Risk of bias
BiasAuthors' judgementSupport for judgement
Random sequence generation (selection bias)Unclear riskSubjects were allocated by block randomisation into 13 clusters but no detail is given about how this process was undertaken.
Allocation concealment (selection bias)High riskAuthor of the trial stated that there was no concealed allocation.
Blinding (performance bias and detection bias)
All outcomes
Low riskNo blinding, but the review authors judge that the outcome and its measurement are unlikely to be influenced by this. Considered low risk.
Incomplete outcome data (attrition bias)
All outcomes
High riskNot all participants attended for biopsy after screening (only 63% of screened positive complied with referral to have a biopsy). These missing data will have increased the risk of bias.
Selective reporting (reporting bias)Low riskProtocol is not available, but it appears that the published reports include all expected and pre-specified outcomes.
Other biasUnclear risk

Positive cases were referred to dentists and physicians to make a diagnosis, but it is unclear whether standardised criteria were used by these clinicians or whether they had received any training in identification of positive lesions.

It is stated that subjects with confirmed oral cancer and PMDs were biopsied and those with confirmed oral cancer were referred. However, although not detailed in the first cycle, only 26.4% of subjects with a PMD had a biopsy in the second cycle and only 26% in the third cycle. It is not clear whether all suspected oral cancer cases did receive a biopsy, but given the definition of "interval cases" in the third paper, it would appear not. In addition, it is stated in the third paper that the reference investigation for final diagnosis was clinical examination by doctors or histology or both. As it is not possible to diagnose early malignancy by visual appearance alone, this may have led to substantial under-reporting of oral cancer. The lack of a histological diagnosis for many of the PMDs also makes it difficult to accurately assess the correct diagnosis and true prevalence of these disorders.

Prevalence of PMD and mortality data is only provided in detail for the first two cycles only. The third paper presents the results over the three cycles from 1996 to 2004 and so does not provide individual detail about the results of the third cycle. It is not clear why this was the case.

Characteristics of excluded studies [ordered by study ID]

StudyReason for exclusion
Allen 1998Letter to author.
Chamberlain 1993Review study.
Chen 2004Uncontrolled clinical mass screening study.
Cheng 2003Randomised controlled trial (diagnostic use).
Eliezri 1988Uncontrolled study (secondary care).
Garrote 1995Uncontrolled study.
Gray 2000Review.
Gupta 1986Non-randomised controlled study.
Gupta 1992Non-randomised controlled study.
Ikeda 1991Uncontrolled study.
Ikeda 1995Uncontrolled study.
Lavelle 2005Review.
Martin 1998Uncontrolled study.
Miller 1988Study in hamsters.
Moyer 1986Uncontrolled study (diagnostic only).
Mullhaupt 2004Non-randomised controlled study.
Nagao 2000Uncontrolled study.
Nagao 2000aUncontrolled study.
Nagao 2003Uncontrolled mass screening study.
Patton 2003Review.
Sankaranarayanan 1997Review study.
Sankaranarayanan 2002Observational, case-control study.
Silverman 1984Uncontrolled study.
Su 2010Community-based randomised controlled trial whose primary aim was to determine whether toluidine blue enhanced the detection rate for potentially malignant disorders.
Vahidy 1972Uncontrolled study.
Zhang 2005Observational study.

Ancillary