Early palliative care for improving quality of life and survival time in adults with advanced cancer

  • Protocol
  • Intervention



This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the efficacy of early palliative care in adults diagnosed with advanced cancer compared with standard cancer care alone.


There have been remarkable improvements in treatments for cancer, but at the time of diagnosis, some patients will still have a reduced life expectancy. Incurable cancer can pose an enormous challenge to the patient, their family, and medical professionals, affecting the patient's quality of life in many ways (Addington-Hall 1995). Interventions tailored to increase the physical and psychological well-being of people with cancer are of utmost importance. Palliative care comprises an "approach that improves the quality of life of patients and their families facing the problem associated with life-threatening illness, through the prevention and relief of suffering by means of early identification and impeccable assessment and treatment of pain and other problems, physical, psychosocial and spiritual" (WHO 2013). Interdisciplinary care and carer support help to deliver the essential elements of palliative care by managing the patient's quality of life and symptom control (Hui 2013). However, although early access is inherent in the definition of palliative care, usual practice is still limited to the terminal phase of illness.

Description of the condition

With an incident rate of 12.4 million cases in 2008 and eight million deaths in 2010, malignant neoplastic diseases remain one of the leading causes of death worldwide (Boyle 2008; Lozano 2012). Globally, the most common entity and cause of cancer-related mortality is breast cancer in women and lung cancer in men. Cancer incidence has been estimated to increase yearly by 1%, with the growing population worldwide and the demographic shift towards an ageing population in developed countries being the paramount factors for future cancer burden (Boyle 2008).

Despite significant progress in understanding the risk factors of cancer, development of methods for the early identification of some cancers or pre-cancerous diseases, and sound advances in the treatment of many cancers previously deemed fatal, cancer continues to cause the premature death of many patients. At the time of diagnosis, the chances of a curative treatment are often minimal due to advanced disease. The American Cancer Society defines advanced cancer as "cancers that cannot be cured" and metastatic cancer as tumours that "have usually spread from where they started to other parts of the body" (American Cancer Society 2013). However, not all advanced cancers are metastatic. For example, brain tumours may be considered advanced because they are not curable and are life threatening, even in the absence of metastasis. In addition, the survival rate of patients remains very poor, especially for metastatic lung cancer as well as pancreatic and biliary tract malignancies.

Because of the upcoming death in many of these cases, it is essential to develop appropriate treatment plans for improving survival, while also aiming for a subjectively worthwhile quality of life. Both symptom control and disease-modifying therapy are used in these situations. By often causing a major decline of physical efficiency and persistent chronic pain, advanced cancer regularly puts the physical and psychological integrity of patients at high risk. In many cases, the correct execution of the necessary medical treatments and the daily routine at home demands continuous familial and often additional external support. Symptoms such as fatigue, anorexia, cachexia, confusion, dysphagia, and dyspnoea are independent prognostic factors for predicting life expectancy in patients with recently diagnosed incurable cancer (Trajkovic-Vidakovic 2012). In addition, patients and their carers are concerned with burdensome existential ruminations leading to psychological distress on both sides, with the long-term risk of severe impairments in patients' and carers' physical and psychological health and declining resources of social support (Moser 2013; Singer 1999). Such developments within the family often promote conflicts about the responsibilities regarding decision-making in therapeutic as well as everyday challenges. Economic consequences frequently comprise, for example, a reduction of family income or considerable out-of-pocket medical spending leading to financial hardship for patients and their families (Elkin 2010; Zhang 2009). Due to these strains, professional support gains extraordinary importance in alleviating physical discomfort as well as in contributing to improving the patient's quality of life.

Description of the intervention

The purpose of palliative care lies in the reduction of suffering and improvement in the quality of life for patients and their carers. According to the current National Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines, palliative care is generally combined with other therapies (such as chemotherapy or radiotherapy) intended to prolong life or reduce symptoms (Levy 2012). Key components of palliative care are as follows: 1. systematic symptom assessment, 2. pain control and relief of other symptoms, 3. psychosocial care, and 4. support for families (Hui 2013; The WHOQOL Group 1998).

Palliative care is administered either by the collaborating of specialists included in a multidisciplinary palliative care team (doctors, clinical nurse specialists, social workers, chaplains, therapists, and psychologists or psychiatrists) or within the scope of a comprehensive care approach co-ordinated by a health professional (often a nurse). Early palliative care can be delivered in a breadth of settings including community, hospitals, and inpatient hospice units. Community hospice services may also support patients earlier in the day care/outpatient setting. Although a systematic review conducted by Hearn 1998 provided some evidence that specialised palliative care teams contribute to improved outcomes in patients as well as in carers, only one study, thus far, has addressed 'team' effects separately from the general effects of a conventional approach and indicated no consistent differences regarding the benefits of both approaches.

Early palliative care begins at the time of or shortly after the diagnosis of advanced disease (Temel 2010). Compared with palliative care, early palliative care is initiated much earlier in the disease trajectory, and it is not bound to the non-response to curative treatment or evident anticipation of death. A prerequisite for patients' readiness for palliative care in such an early situation is coherent and empathetic communication of health professionals (de Haes 2005; Dowsett 2000; Meyers 2003; Morrison 2004; Sinclair 2006). The purpose of early palliative care is to outline realistic and attainable goals of treatment (Van Mechelen 2013), and to facilitate patient choices by providing adequate information and assessment of his/her values and preferences with regard to advance care planning (Levy 2012). The underlying idea is that symptoms treated early can be managed more easily, thereby improving the patients' quality of life.

How the intervention might work

With a focus on intensified doctor-patient communication, early palliative care may lead to higher social support and increase the likelihood of the acceptance of the diagnosis and illness severity. These effects, along with the augmented satisfaction of the patient-physician relationship, may improve the patient's openness to symptom control and psychosocial interventions, thereby reducing distress. Reduced distress itself is associated with improved quality of life and consistently associated with survival (Gotay 2008; Irwin 2012; Pinquart 2010). Furthermore, patient and family members undergoing early palliative care are better informed about treatment directives and end-of-life decisions, which promotes the experience of higher self efficacy and a higher sense of control in decisions with respect to their individual values (McClain 2003). On the one hand, better symptom control and psychosocial function could promote better adherence to reasonable treatment plans. On the other hand, palliative care is linked to less aggressive cancer treatment, such as reduced use of questionable chemotherapy and treatment in intensive care units (Earle 2008). This tendency to de-escalate treatment intensity in final, irreversible health conditions, together with the extension of outpatient and community palliative care services, is important to patients as well as to socioeconomics (Lowery 2013; Smith 2003).

Why it is important to do this review

Evidence for the benefits of late palliative care is ambiguous because the time required for establishing the beneficial effects may be too short (El-Jawahri 2011; Gomes 2013; Higginson 2010; Zimmermann 2008). Palliative interventions applied early, around the time of the diagnosis of incurable advanced cancer, may be more favourable to improve symptom and disease management (Levy 2012). Therefore, some investigators consider there is a paradigm shift (Kelley 2010). To date, no systematic review or meta-analysis has been conducted on early palliative care interventions for patients with advanced cancer. This results in both a lack of an overview of interventions applied within this framework as well as uncertainty about the general impact of such interventions on various patient- and carer-related outcomes.


To assess the efficacy of early palliative care in adults diagnosed with advanced cancer compared with standard cancer care alone.


Criteria for considering studies for this review

Types of studies

We will include randomised controlled trials (RCT) or cluster-randomised trials.

Types of participants

Patients will be eligible if they are diagnosed with a malignant tumour entity in an advanced stage (assessed by the oncologist and based on the disease stage and tumour type) and without curative treatment options (i.e. due to metastatic disease or inoperability, or both). In accordance with the definition of the American Cancer Society 2013, we will define advanced cancer as 'cancers that cannot be cured' and that, in the case of metastatic cancer, tumours 'have usually spread from where they started to other parts of the body'. In all malignant entities, limited prognosis can be a common disease consequence and, therefore, constitute the main eligibility criteria for the inclusion of participants. Estimates of patients' survival must be for two years or less. We will not include disabled long-term survivorship patients, although such patients may also be in need of early palliative care. Assessment of the prognosis must be based on the disease stage as an objective clinical indicator, in conjunction with the clinician's estimation conducted by the primary oncologist. We intend to consider only studies on adults, aged 18 years and older, for inclusion and exclude adults diagnosed during childhood and people already in the terminal phase of illness (predicted survival of less than three months with eligibility for hospice care) at study inclusion.

Types of interventions

As defined in a previous study (Zimmermann 2008), we will include all types of professional palliative care services that provide or co-ordinate comprehensive care for patients in early advanced stages of cancer. In addition, care has to be multidimensional (i.e. the intervention has to target at least the 'physical' and 'psychological' domain of quality of life). We intend to exclude studies evaluating the impact of only one domain of quality of care (e.g. medication on pain or psychological interventions on depression). We will not include stand-alone palliative therapies modifying the disease to prolong life (e.g. palliative chemotherapy) or relief symptoms (e.g. palliative radiotherapy). We will apply no restrictions on the type of delivery (inpatient/outpatient) or place of consultation (clinic, patient's home). The active comparator will be treatment as usual/standard cancer care (i.e. no systematic palliative treatment or delayed or late palliative care).

Types of outcome measures

Primary outcomes

Primary outcomes and corresponding measures will be:

  • health-related quality of life (e.g. measured using Functional Assessment of Cancer Therapy (FACT), City of Hope Quality of Life Questionnaire, European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (EORTC QLQ-C30), McGill Quality of Life Questionnaire, 36-Item Short Form Health Survey (SF-36), Supportive Care Needs Survey (SCNS));

  • depression (e.g. measured using Beck Depression Inventory (BDI), Hamilton Rating Scale for Depression (HAM-D), Hospital Anxiety and Depression Scale (HADS), Patient Health Questionnaire (PHQ-9), Centre for Epidemiological Studies - Depression Scale (CES-D));

  • symptom intensity (e.g. measured using Edmonton Symptom Assessment Scale (ESAS), Brief Pain Inventory (BPI));

  • survival.

Outcomes should be measured through self report questionnaires, patient records, or interviews with measures of adequate psychometric properties. Scales should be continuous or time-to-event for survival.

The most relevant time points to measure outcome will be 'medium-term' (one to four months after initiation of early palliative care) for self rated outcomes and 'long-term' for survival.

We will present a 'Summary of findings' table that will include for each of the seven outcomes information on outcome with intervention as well as with comparator, number of participants, quality of evidence, and comments (e.g. clinical importance of results, contextual factors), as set out in the author guide of the Cochrane Pain, Palliative and Supportive Care group (AUREF 2012).

Secondary outcomes

We will assess three categories of secondary outcomes:

  • carer burden as a carer-related outcome (e.g. measured using Caregiver Strain Index (CSI), Supportive Care Needs Survey for Partners & Caregivers (SCNS-P&C), BDI, HAM-D, PHQ-9, CES-D);

  • healthcare utilisation (e.g. measured using length of hospital stay in days, number of outpatient attendances, direct or indirect medical resource use) as an economic outcome;

  • adverse events (measured as binary outcome 'Any adverse event (yes/no)').

Search methods for identification of studies

We will conduct a highly sensitive literature search to identify eligible studies. Two review authors (MWH and SE) will document the search process and the records, and assess potentially relevant studies, as well as making the final selection for inclusion and data extraction. Generally, we will resolve disagreements by discussion and, if necessary, by consultation with an arbiter (MH).

Electronic searches

We will search the following electronic databases:

  • Cochrane Central Register of Controlled Trials (CENTRAL, The Cochrane Library);

  • MEDLINE (Medical Literature Analysis and Retrieval System Online) via OvidSP;

  • EMBASE via www.embase.com;

  • PsycINFO via OvidSP;

  • CINAHL (Cumulative Index to Nursing and Allied Health Literature) via EBSCO;

  • Opengrey (European Association for Grey Literature Exploitation EAGLE) (www.opengrey.eu) via EXALEAD.

We will use free-text search of titles, abstracts, and keywords, as well as medical subject headings (MeSH) during searches. We will run the search from the earliest publication date possible in each database. We will apply no restrictions regarding language. We will tailor searches to individual databases. The full search strategy for MEDLINE is in Appendix 1. In addition, we will search citations of key authors via Web of Science and PubMed's 'related article' feature. Joanne Abbott, the Trial Search Coordinator of the Cochrane Pain, Palliative and Supportive Care Group and Maria-Inti Metzendorf (Library for the Medical Faculty of Mannheim, Heidelberg University) supported the compilation of the search strategies.

Searching other resources

We will search the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) (apps.who.int/trialsearch/) for ongoing trials. This database includes ClinicalTrials.gov (www.clinicaltrials.gov) and the metaRegister of Controlled Trials (mRCT) (www.controlled-trials.com/mrct). In addition, we will check reference lists of reviews and retrieved articles for additional studies and perform citation searches on key articles. We will contact experts in the field for unpublished and ongoing trials.

Data collection and analysis

Selection of studies

During the database searches, we will download all retrieved records, including abstracts, and compile them by using the reference manager Endnote X6. We will remove duplicate records of the same report. During the next step, two independent review authors (MWH and SE) will screen titles and abstracts and exclude records obviously not fulfilling the inclusion criterion. For the remaining studies marked as potentially relevant by either review author, we will obtain the full-text documents and check for eligibility. To ensure the reproducibility of the judgements regarding the studies to be included, we will extract the titles and abstracts and two unblinded independent raters (MWH and SE) will assess them. For formal measuring agreement, we will calculate the simple kappa statistic to evaluate the need for reconsidering the eligibility criteria. We will resolve singular disagreements by discussion and, if necessary, by consultation with an arbiter (MH). We will link multiple reports of the same study together. We will compile a list of excluded studies and provide the primary reason for their exclusion. We plan to include a PRISMA study-flow diagram in the full review to document the screening process (Liberati 2009), as recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Schünemann 2011).

Data extraction and management

Two review authors (SE and MWH) will set up the data collection form and coding instructions in accordance with the checklist proposed by The Cochrane Collaboration (Higgins 2011a, Table 7.3.a). Two unblinded independent review authors (MWH, as topic area specialist and SE, as methodologist) will collect data from published study reports using an electronic version of the data collection form. We will resolve disagreements by discussion and, if necessary, by consultation with an arbiter (MH). For the completion of study details or missing numeric results, we will contact study authors when necessary. For the meta-analysis of continuous outcome variables, we will extract the mean value and standard deviation of the outcome measurements as well as the number of participants in each intervention group. For time-to-death outcomes, we will obtain estimates of log hazard ratios and their standard errors (Tierney 2007). One review author (SE) will enter the data into into Review Manager 5 (RevMan 2012) and a second review author (MWH) will verify entries. For cluster-randomised trials, we will use the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). We plan to collect the characteristics of included studies in sufficient detail to produce a 'Characteristics of included studies' table in the full review.

Assessment of risk of bias in included studies

We will apply the Oxford Quality Score as the basis for inclusion (Jadad 1996), limiting inclusion to studies that are, as a minimum, randomised controlled or cluster-randomised. Blinding of participants and personnel will not be mandatory for inclusion, because it is often not feasible in palliative care studies. In addition, we will not consider blinding of assessors because most studies use self report questionnaires for primary outcome assessment. Furthermore, high attrition rates will not lead to exclusion, as these are to be expected in palliative care studies.Two unblinded independent review authors (MWH and SE) will conduct a domain-based evaluation by using The Cochrane Collaboration's tool for assessing the risk of bias (Higgins 2011c). The data collection form will include five specific domains, random sequence generation, allocation concealment, incomplete outcome data, selective reporting, and other bias. For cluster-randomised studies, we will assess the risk of bias with regard to recruitment bias, baseline imbalance, loss of clusters, incorrect analysis, and comparability with individually randomised trials. For each study, the results will be presented in a 'Risk of bias' table.

Measures of treatment effect

In anticipation of different scales being applied across studies, we will use standardised mean differences as effect measures for continuous data of the primary outcomes health-related quality of life, emotional distress, and symptom intensity. We will analyse time-to-event data (survival duration) as hazard ratio under the proportional hazards assumption that hazard ratio is constant across the follow-up period. Similarly, with regards to secondary outcomes, we will apply standardised mean differences for carer burden as well as for healthcare and resource use.

Unit of analysis issues

Unit of analysis issues may arise because in early palliative care studies results may be presented for several periods of follow-up and because in cluster-randomised trials, groups of patients instead of individual patients are randomised. We will address the issue of several periods of follow-up by restriction to a single point of measurement for each outcome, as described in Primary outcomes. For cluster-randomised studies, we will use adjusted effect measures. In case of more than two parallel intervention arms, we will consider only two arms (preferably the early palliative care arm versus standard care).

Dealing with missing data

Whenever possible, we will ask the original investigators to provide any missing data. In palliative care settings, missing data may not be missing at random but may often indicate poor outcomes; thus, a simple replacement method does not seem adequate. We ultimately will replace values assuming negative outcomes for the experimental group and positive outcomes for the control group. We will address the potential impact of missing data in the 'Discussion' section.

Assessment of heterogeneity

We will investigate the variation in effects observed across studies by using a Chi2 test included in forest plots, with regards to the total number of identified studies. For further quantification of inconsistency across studies, we will calculate the I2 statistic. We expect heterogeneity due to different scales, patient populations, clinical settings, and type of interventions. Subsequently, we will explore heterogeneity by conducting subgroup analyses of the clinical and methodological factors.

Assessment of reporting biases

We will perform comprehensive database searches, including those of grey literature, to reduce the risk of reporting bias. We will employ funnel plots that plot the standard error of intervention effect estimate against standardised mean differences to identify small-study bias. If appropriate test power is ensured by a sufficient number of included studies (k > 10), we will perform Egger's test (Egger 1997). In case of small-study effects, we will explore probable explanations, compare fixed-effect and random-effects estimates of the intervention effect, and cautiously interpret the results.

Data synthesis

Statistical analysis of study findings will include pair-wise comparisons regarding differences in the anticipated continuous primary patient-related outcome data on health-related quality of life, emotional distress, and symptom intensity between early palliative care interventions and a control condition. Standardised mean differences will be specified as measures of intervention effect. To clarify if there is evidence for benefit from early palliative care interventions overall, we intend to perform a meta-analysis based on an inverse variance random-effects model with a sufficiently homogeneous group of studies (DerSimonian 1986). In case of extreme variation in results, we will not perform a meta-analysis.

Subgroup analysis and investigation of heterogeneity

We will conduct subgroup analyses applying prespecified explanatory variables. These will be 1. specialised care team versus other models of early palliative care and 2. samples with a single type of tumour versus samples with various tumour types.

We will perform a meta-regression to explore a dose effect of intervention on outcome variables if a sufficient number of included studies (k > 10) is present. We will highlight the observational character of subgroup analysis results and avoid definitive conclusions.

Sensitivity analysis

If there is considerable heterogeneity (I2 statistic > 70%), we will perform a sensitivity analysis by re-running the meta-analysis while excluding one study at a time to identify outlying studies and to investigate the robustness of the pooled effect estimate.


We would like to thank Sabine Sommerfeldt for her contribution to the development of this protocol. We would also like to thank Maria-Inti Metzendorf (Library for the Medical Faculty of Mannheim, Heidelberg University) for contributing to the search strategies.


Appendix 1. MEDLINE (OvidSP)

1. exp Palliative Care/

2. palliat*.tw.

3. "advanced disease*".tw.

4. ("end-stage disease*" or "end stage disease* or end-stage illness" or "end stage").tw.

5. Terminally Ill/

6. Terminal Care/

7. (terminal* adj6 care*).tw.

8. ((terminal* adj6 ill*) or terminal-stage* or dying or (close adj6 death)).tw.

9. (terminal* adj6 disease*).tw.

10. (end adj6 life).tw.

11. hospice*.tw.

12. or/1-11

13. exp Neoplasms/

14. (neoplasm* or cancer* or tumo?r*).tw.

15. or/13-14

16. 12 and 15

17. randomized controlled trial.pt<http://trial.pt>.

18. controlled clinical trial.pt<http://trial.pt>.

19. randomized.ab.

20. placebo.ab.

21. clinical trials as topic.sh.

22. randomly.ab.

23. trial.ti.

24. 17 or 18 or 19 or 20 or 21 or 22 or 23

25. exp animals/ not humans.sh.

26. 24 not 25

27. 16 and 26

Contributions of authors

All authors will be involved in setting up the review, the selection of studies, and writing of the review.

Declarations of interest

There are no conflicts of interest.

Sources of support

Internal sources

  • Heidelberg University Hospital, Germany.

    Employer of MWH, SE, HCF, MT, and MH

  • University Medical Center Freiburg, Germany.

    Employer of GR

External sources

  • No sources of support supplied