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Keywords:

  • multiple myeloma;
  • quality of Life;
  • outcome assessment;
  • psychometrics;
  • review

Abstract

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Conflicts of interest
  8. References

Introduction

Treatment advances in multiple myeloma have increased expected survival from months to years for some patients. Alongside improved survival emerges a need to better understand and measure health-related quality of life (HRQOL), both in research and clinical settings.

Objectives

(i) Identify HRQOL tools validated for use in myeloma; (ii) identify issues important to HRQOL from the point of view of patients with myeloma; (iii) describe the measurement properties of each HRQOL tool; (iv) evaluate the content validity of HRQOL tools in terms of their ability to capture all issues important to patients and (v) explore the suitability of each HRQOL tool for use in different settings.

Method

Systematic literature review of six databases with no limits by date or language.

Results

Thirty-nine studies reported validation of 13 HRQOL instruments. Seven studies identified issues important to HRQOL from the patients' perspective. No instrument was comprehensive to all issues important to patients. The EORTC-QLQ-C30 and MY24 have undergone the most comprehensive psychometric validation. Most validation occurred in trial patients and not clinically representative groups. No studies evaluated clinical utility of tools alongside routine practice.

Conclusion

The best existing HRQOL tools are designed predominantly for use in research. Reliable, valid and responsive tools exist for this purpose, but may miss issues important to patients. The design of HRQOL measures should be guided by intended utility, whether for research or clinical practice, and further validation of HRQOL tools in clinically representative groups is needed. Development and validation of HRQOL tools for clinical use may be of value.

Multiple myeloma (MM) is the second most common haematological malignancy in the UK, with an age standardised incidence of 5.3 per 100 000 in 2008 [1]. Recent years have seen improvements in survival with the routine use of high-dose therapy and autologous stem cell transplant, the introduction of novel therapies, and improved supportive care. These approaches have prolonged median overall survival to about 5–7 years [2], although a cure remains elusive.

Maintaining good health-related quality of life (HRQOL) is an important goal in the care of people with myeloma. Improvements in survival have created a greater need to understand the longer-term impact of disease and treatment on HRQOL. The complex pattern of end organ damage seen in myeloma, coupled with the side effects of treatment can affect all domains of HRQOL, including physical symptoms such as fatigue and pain, concerns about the future, changes in body image and disturbed role function [3]. There is also evidence that patients with myeloma report more symptoms and problems than those with other haematological cancers [4].

A previous systematic review of randomised controlled trials (RCTs) in myeloma identified only 15 trials reporting HRQOL as a study end point [5]. This relative lack of published myeloma-specific HRQOL data is also impacting on the utility of other trial data, and assessment by regulatory bodies when making difficult decisions around the funding of new drugs. This review identified 12 different HRQOL tools used across the 15 trials, which also highlights the lack of consensus on the best instrument to use. Some instruments have been developed or validated in mixed haematological or cancer samples, and it is not known to what extent they capture the issues important to HRQOL from the point of view of patients with myeloma.

Health-related quality of life instruments can be used in clinical research, health economic evaluations and also in clinical practice. Clinical applications of HRQOL tools may include prognostication, monitoring response to treatment, prioritising problems or facilitating communication [6-8]. The use of HRQOL instruments in clinical practice has also been shown to independently improve HRQOL in general oncology patients [9]. Some authors who have demonstrated reduced HRQOL in myeloma have concluded that HRQOL assessment should become a normal part of clinical care [3, 10, 11]. Yet, this remains uncommon in myeloma, and it is not known what instrument would be best suited for this purpose.

We report a systematic review of the literature to identify and evaluate all existing HRQOL tools developed or validated for use in myeloma. The rationale for this review is to provide researchers and clinicians with an overview of all the instruments available, and to help users select the best tool for use in a given setting.

Objectives of the review are (i) identify HRQOL tools validated for use in myeloma; (ii) identify issues important to HRQOL from the point of view of patients with myeloma; (iii) describe the measurement properties of each HRQOL tool; (iv) evaluate the content validity of each HRQOL tool in terms of its ability to capture all the issues important to patients and (v) explore the suitability of each HRQOL tool for use in different settings.

Methods

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Conflicts of interest
  8. References

Literature search

The methods of literature identification are outlined in Fig. 1. Database searches were carried out to cover biomedical sciences (MEDLINE 1950 – Present); mental health (PsycINFO 1806 – Present); pharmacology (EMBASE 1980 – Present); nursing and allied health (CINAHL 1981 – Present), nursing and midwifery (BNI 1984 – Present); and complimentary and allied medicine (AMED 1985 – Present).

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Figure 1. Outline of methods used for study identification including inclusion and exclusion criteria.

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Search terms are shown in Fig. 1 and were designed to capture studies with patients with myeloma at all stages of disease and in different settings. Final search terms varied for each of the six databases in line with the different Medical subject (MeSH) headings used in each case. Searches were run without date or language limits on 28 September 2010 and updated on 18 November 2011. Note that we carried out a parallel review of HRQOL tools in follicular lymphoma from the same database search (to be reported separately). This is reflected in the search terms.

To account for database limitations, six key journals were searched manually on 27 February 2011 and again on 30 November 2011. We also carried out reference and citation searching of all included articles and relevant review articles. This was performed using Scopus on 1 April 2011 and updated on 2 December 2011.

Study identification

Different types of article were required to address objectives (i) (identify HRQOL tools) and (ii) (identify relevant HRQOL issues). We used a novel approach reported elsewhere [12], whereby one main literature search was used, and each citation judged against two sets of inclusion and exclusion criteria – the Tools Criteria and Issues Criteria (Fig. 1).

The Tools Criteria were designed to identify all studies reporting development or validation of a multidimensional HRQOL tool in myeloma. Mixed samples of >25% myeloma were included to capture studies where patients with myeloma fall within a mixed cancer or haematology sample (e.g. validation of a HRQOL instrument in a mixed sample of bone marrow transplant recipients). A multidimensional HRQOL instrument was defined as any quality of life instrument assessing two or more of the three core domains described by the World Health Association: physical, social and psychological well-being [13]. This did not include instruments assessing more narrow constructs such as pain, even if it assessed physical and psychosocial effects. Multidimensional measures of health status were included despite the argument that these are distinct from measures of HRQOL [14]. It was felt that health status instruments should be included as they are important outcome measures often used in health care.

The Issues Criteria were designed to identify studies exploring the issues important to HRQOL from the patients' perspective. Studies were included if they used inductive (usually qualitative) methods. Those using existing structured scales to assess HRQOL were excluded because they make assumptions about what is important to patients. Only studies with samples of 100% myeloma were included to maintain focus on the particular experience of patients with myeloma.

All citations were imported into Endnote X3 following the database search. Duplicate articles were identified using the automated function and checked visually before exclusion. Citations were screened against both sets of inclusion/exclusion criteria by two reviewers (TO or CR). Each citation was screened first by title and abstract, then by full text.

Data extraction and analysis

Details of study design and sample were extracted for all included articles using a piloted data extraction form. All data extraction was carried out by two independent reviewers (TO and CR) and discrepancies resolved by consensus. Articles included under the Tools Criteria were used to construct a summary table of all HRQOL tools developed or validated in myeloma, with measurement properties extracted under the headings shown in Table 1.

Table 1. Criteria used to describe measurement properties of health-related quality of life (HRQOL) instruments (adapted from those reported elsewhere, [12])
  1. a

    Criterion validity has been defined as ‘the correlation of a scale with some other measure of the trait or disorder under study, ideally a ‘gold standard’ which has been used and accepted in the field’ [64]. As there is no accepted gold standard HRQOL instrument for use in myeloma, this poses a challenge for demonstrating criterion validity. Correlations with another widely used scale are presented here under the umbrella of criterion validity.

Validity
Content validity: does the instrument cover the issues of importance to patients?
Criterion validity: does the instrument correlate with superior measures?a
Construct validity: do results confirm expected pattern of relationships or hypotheses?
Reliability
Internal consistency: do individual items within the instrument correlate with each other and with total scores?
Test–retest reliability: does the instrument produce the same results when applied under the same conditions at different times?
Responsiveness and floor/ceiling effects
Does the instrument discriminate between differing degrees of disease severity?
Has the instrument demonstrated change in clinical trials or longitudinal studies?
Are observed scores well distributed around scale midpoint, with low floor and ceiling effects?
Minimal important difference and prognostication
What score change corresponds to a meaningful change to the patient?
Is the instrument able to predict clinical outcomes such as survival?

Articles included under the Issues Criteria were quality assessed for methodological rigour using a checklist reported by Hawker et al. [15]. This checklist rates nine components of each article as Good (score 3), Fair (2), Poor (1), or Very Poor (0), giving an overall score of 27 for each article.

Emergent themes identified in each article were extracted and used to generate a list of issues important to HRQOL. Two reviewers (TO and CR) each independently extracted a long list of potential issues from the included articles. From these long lists, each reviewer independently grouped related issues together to produce a summary list (e.g. grouping together ‘pain’ and ‘fatigue’ as ‘disease-related symptoms’). The two summary lists were then compared and differences resolved by consensus to arrive at a final list of HRQOL issues. This list was then used to evaluate the content validity of each HRQOL tool.

Suitability of HRQOL tools for use in different settings

The samples and settings used for psychometric validation were recorded, allowing an assessment of how well each tool can be generalised for use in different settings.

Each tool was also assessed in terms of whether it elicits perceptions of health status (e.g. ‘What is your current level of pain from 1 to 10?’), or health evaluations (e.g. ‘How much does pain currently interfere with your life from 1 to 10?’). This distinction has been described in detail by Ferrans [14], and its implication for the utility of HRQOL tools in different settings is considered in the discussion below. Each question on each tool was assessed as eliciting health status or health evaluation by two independent reviewers (TO and CR) with discrepancies resolved by consensus. Items asking about the presence, absence or size of a problem were categorised as perceptions of health status. Items asking respondents to make a judgement about satisfaction, worry, contentment or any other emotional response to a problem were considered as health evaluations. Pain was considered to be both a disease-related symptom and a treatment-related symptom. Items asking about ‘usual activities’ were considered to encompass hobbies, leisure, employment or any other activity involving participation.

Results

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Conflicts of interest
  8. References

The database search identified 12 270 articles. Thirty-nine articles met the Tools Criteria and reported some validation of a HRQOL instrument in myeloma [3, 10, 11, 16-51]. Seven articles met the Issues Criteria and used inductive methods to identify HRQOL issues important to patients with myeloma [43, 52-57]. One article reported the development of a myeloma-specific HRQOL module (the EORTC-QLQ-MY24) and met both sets of criteria [43]. Figure 2 shows the sources of included articles and main reasons for exclusion at each stage (as per PRISMA recommendations, [58]).

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Figure 2. PRISMA Chart showing identification of included articles and reasons for exclusion.

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Identification of HRQOL tools

Thirteen different HRQOL instruments were identified across the 39 included studies. In 16/39, the study's primary aim was to develop or in some way appraise a HRQOL instrument. The remaining 23/39 studies simply used a HRQOL instrument but also reported some instrument properties (e.g. a descriptive study of HRQOL or within an RCT). Table 2 shows a summary of the sample and design characteristics of studies reporting validation of HRQOL instruments in myeloma, and the range of instruments identified.

Table 2. Sample and design characteristics of studies reporting validation of health-related quality of life (HRQOL) instruments in myeloma, showing the range of instruments identified
 Studies with primary aim to develop or appraise a HRQOL instrumentTrials and descriptive studies reporting some validation of a HRQOL instrument
  1. For key to abbreviations of instruments see Table 5.

Sample 100% myeloma (or mixed sample with separate validation data reported for myeloma subgroup)

EORTC-QLQ-C30

EORTC-QLQ-MY20 and MY24

EQ-5D, 15D

EORTC-QLQ-C30

EORTC-QLQ-MY20 and MY24

FACT- BMT, EQ-5D, SF-12

Mixed sample with >25% myeloma

EORTC-QLQ-C30

EORTC-QLQ-HDC19

FACT-BMT, LIP, SEIQoL-DW

EORTC-QLQ-C30

EORTC-QLQ-HDC19

FACT-BMT, FACT-An, QLI, SEIQoL-DW, SF-36

Only one disease-specific instrument was identified (EORTC-QLQ-MY24/MY20). Other measures were general cancer tools (EORTC-QLQ-C30, FACT-An), treatment specific (EORTC-QLQ-HDC19, FACT-BMT), or generic [SF-36, SF-12, SEIQoL-DW, EQ-5D, 15D, life ingredient profile (LIP), Quality of Life Index (QLI)]. The SEIQoL-DW was the only individualised instrument (with domains defined by respondents). No instrument was developed specifically for clinical use, or in palliative settings – although the search strategy was designed to identify these.

Identification of HRQOL issues important to patients

Seven articles used inductive methods to identify HRQOL issues important to patients with myeloma. 6/7 were qualitative studies exploring lived experience [53, 56, 57]; trauma and post-traumatic growth [52]; illness experience and unmet needs [54]; and distressing experiences [55]. The remaining 1/7 reported the development of a myeloma-specific HRQOL module (the EORTC-QLQ-MY24, [43]). Table 3 presents the design, findings and methodological quality of these seven studies. Table 4 shows the summary list of important HRQOL issues that was derived from these studies.

Table 3. Summary of studies used to support content validity of health-related quality of life (HRQOL) instruments, showing the themes and issues important to people with myeloma
Author, Year, AimMethod usedSampleQuality scoreaSummary of themes and issues generated:
  1. Key to abbreviations: HSCT, haematopoetic stem cell transplant; US, United States; UK, United Kingdom; MM, multiple myeloma).

  2. a

    Score of methodological quality taken from Hawker et al. (appendix D, [15]). Total score of 27 reached by rating nine components of each article as Good (3), Fair (2), Poor (1) or Very Poor (0). The following were the nine components rated: Abstract and title; Introduction and aims; Method and data; Sampling; Data analysis; Ethics and bias; Results; Transferability and generalisability; Implications and usefulness.

Stead et al. (1999) [43]

‘To develop a questionnaire with a maximum of 30 items to assess the disease-specific symptoms of myeloma and their impact on daily life, and treatment-related issues, mainly side effects of chemotherapy’

Relevant issues generated by literature review (up to 1995) and ‘informal interviews’ with patients and healthcare providers

Second sample of patients and professionals then used to confirm the relevance of each issue

No details reported of sample used for informal interviews during generation of issues

Second sample, n = 40, 10 each from UK, Norway, Denmark and Sweden. Twenty male, 20 female. Range of time since diagnosis

10/27

1. Disease symptoms

Bone aches, back pain, pain in hip, pain in arm or shoulder, chest pain, pain increasing with activity

2. Treatment side effects

Drowsiness, thirst, feeling ill, dry mouth, hair loss, upset by hair loss, tingling in hands and feet, restlessness/agitation, acid indigestion/heartburn, burning or sore eyes

3. Social support

Relationships with doctors, care received from doctors, information about illness, feeling of being listened to, physical attractiveness, thinking about illness

4. Future perspective

Worried about dying, worried about health in the future

Dahan et al. (2006) [52]

‘To understand the emotional impact of multiple myeloma, as well as the impact of its principle treatment, peripheral blood stem cell transplant’

Semi-structured qualitative interviews. Questions about time leading to diagnosis, reaction to diagnosis, transplant experience, relationships with doctors, support from others, impact of illness on others, spiritual affiliation, sexuality and body image, cancer centre experience and changes to selfUS, n = 6, mean age 57.3 years (range 50–66). Three male, 3 female. Five Caucasian, 1 African American. All had undergone HSCT at least 3 months prior18/27

1. Diagnosis

Catalysts to diagnosis (feeling generally unwell, pain, frustration at delayed diagnosis), looking death in the face, deciding a plan of action (importance of specialist care and the right amount of information)

2. Treatment

Reaction to transplant (physical and emotional suffering), physical immobilisation (weakness, fatigue, reduced libido and impaired sexual function), violation and dehumanisation (reduced strength, hair loss, reduced intellect, reduced leisure/hobbies), isolation (social withdrawal, breakdown of relationships with family and friends), vulnerability (changes in physical appearance being a threat to privacy, medical error), burden on family

3. Network of safety

Confidence in doctor, importance of specialist care, social support, family support, support from patients, personal coping

4. Recuperation

Strengthening of body and spirit (increasing physical vitality helps restore the emotional state)

5. Reflection/new existence

Changed body (weight gain, short-term memory loss, insomnia, fatigue, painful neuropathy, diminished and attractiveness), reduced hope, enduring threat of relapse, anticipating loss, acceptance, resilience and strengthened connection to others

Molassiotis et al. (2011) [54]

‘To explore [the longer-term difficulties experienced by patients with myeloma] after completion of treatments, and to obtain a more in-depth understanding of the concerns, challenges and issues that may dominate life with myeloma’

Semi-structured qualitative interviews. Questions around challenges of coping with the illness, positives of having MM, comparisons with people of a similar age not living with myeloma and unmet needsUK, n = 20, mean age 61.8 years. Eight male, 12 female, all white British. Twelve previously received HSCT. Mean 5 years since diagnosis (range 1–11.5)26/27

1. Current and future concerns

Fear and uncertainty about the future, decreased independence, role changes, frustration, difficulty accepting illness, further concerns around specific health problems (hearing loss, constipation, height loss, pain)

2. Effects of myeloma on daily life

Physical effects (tiredness, pain, visual problems, hearing loss), role changes, changes to social function, effects in working life

3. Practical, functional and emotional coping

Use of aids – positive/negative views, information needs, carrying on with life, keeping active, titrating pain medication (including worry about tablet burden and side effects), importance of family support, ability to cope

4. Unmet needs

Limited help from outside agencies (and difficulty accessing help), lack of community care, importance of seeing the person in the patient (including lack of continuity of care and seeing a different doctor each visit)

Potrata et al. (2011) [55]

‘To gain greater insight into symptoms and distressing experiences of patients living with myeloma, to understand what can distress patients and how we can support them better in practice’

Qualitative interviews. Questions focussed on symptom experience, related distress and how having MM impacted on everyday life, body image, social life and relationships

UK, n = 15, mean age 58.2 years (range 42–75). Ten male, 5 female

11 white, 4 ethnic minority

11 had previously received HSCT

9 were over 5 years since diagnosis

23/27

1. Distress from experienced symptoms

Brittle bones, impaired mobility, reduced independence, financial concerns, tiredness and lethargy, nausea, pain

2. Distress from body image changes

Weight loss or gain, hair loss, loosing height

3. Distress caused by family and friends

Importance of support from friends and family, being reminded of one's condition causing distress, financial difficulties

4. Distress from myeloma-related information

The need for the right amount of information

5. Distress from stem cell transplant

Nausea, insomnia, inability to swallow, mucositis, fear of dying

Maher & De Vries, 2001 [56]

‘To explore the experiences of eight people living with relapsed myeloma,

specifically to explore how the experience of living with relapsed myeloma had affected the quality of the lives of these individuals’

Unstructured qualitative interviews conducted in a conversational manner to elicit narrative data

UK, London teaching hospital, n = 8. Age range, 48–74

5 male, 3 female. Purposive sampling to select only those with relapsed disease

14/27

1. Living with uncertainty (cited as the dominant overarching theme)

Affect of uncertainty on future and daily routine, uncertainty due to both disease and treatment, apprehension and worry about test results, re-evaluation of life and priorities, not being able to plan for the future

2. Intuitive knowing

Alongside uncertainty about the future was knowledge (certainty) that the illness had relapsed before being told by a clinician

3. Maintenance of normality

Living a normal life vital to coping with uncertainty, acceptance that family and friends avoided discussing the illness, reluctance to share true feelings to maintain normality

4. Adjustment to illness

Recognising limitations, importance of support from family, disintegration of some and friend unable to provide support, physical and psychological stress, impact on activities of daily living, anxiety and depression leading to social isolation

5. Hope

Coping with uncertainty, importance of spiritual beliefs, and importance of potential new treatments giving an ‘illusion or safety’

6. Effects of treatment

Toxicity of treatment – infection, neuropathy, pain, nausea, fatigue

7. Trusting healthcare professionals

Importance of information in reducing uncertainty, feeling valued if concerns listened to, importance of confidence in the team

8. Fighting spirit

An important coping mechanism – to remain ‘strong’ and ‘brave’

Kelly & Dowling 2011 [57]

‘To explore patients’ lived experience of being diagnosed with myeloma, to provide haematology and oncology nurses with greater insight into the care requirements and needs of this patient group’

Qualitative interviews focussing on the experience of living with myeloma

Ireland, regional specialist centre, n = 11, mean age, 63 (range, 42–83)

7 male, 4 female. Time since diagnosis 1.5–4 years

19/27

1. Lived body: a changed body

Alopecia, fatigue

2. Lived space: living in limbo

Living with an ‘unknown’ cancer, stigma of cancer, loss, feeling ‘lucky’

3. Lived time: time is precious

Fear or recurrence, limited time with healthcare professional

4. Lived relations: significance of support

Family support, protecting others

Vlossak & Fitch 2008 [53]

‘To explore in a qualitative manner the impact of a diagnosis of myeloma on the patient and family’

Qualitative telephone interviews focussing on experiences specific to living with myelomaConvenience sample, regional cancer centre, Ontario, US. N = 20, age range 44–88, 13 male, 6 female. Time from diagnosis 10 months–6 years18/271. Shock of diagnosis
2. Few options for treatment
3. Worry about family
4. Treatment is difficult, long, complex
5. Fatigue is overwhelming
6. Loss of independence
7. Change in self concept/self image
8. Obsession about how and when the end will come
9. Fear of recurrence
10. Rationalisation of changes in hopes for the future
Table 4. Showing [1] issues important to the health-related quality of life HRQOL of patients with myeloma; [2] comprehensiveness of each HRQOL questionnaire; and [3] type of information elicitedThumbnail image of

Measurement properties of HRQOL tools

A summary of the measurement properties of the 13 HRQOL instruments is shown in Table 5. This gives details of the samples used for validation, and outlines the measurement properties reported from each sample. Although the EORTC-QLQ-MY20 is a subsequent version of the MY24, they are considered separately for clarity.

Table 5. Measurement properties of health-related quality of life (HRQOL) instruments identified and samples used for validation
Instrument NameSubscales and total itemsSample detailsValidityReliabilityResponsiveness and floor/ceiling effectsMinimal important difference and prognostication
  1. Abbreviations for instruments are given within the table.

  2. Key to other abbreviations: HSCT, haematopoetic stem cell transplant; US, United States; UK, United Kingdom; MM, multiple myeloma; MID, minimal important difference; QOL, quality of life; VAS, visual analogue scale; SRM, standardised response mean, the mean score change from baseline to follow-up divided by standard deviation of the change.

European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire – Core (EORTC-QLQ-C30, [10, 16, 21-28, 30-35, 37, 39, 41, 44-47, 49-51])

5 functional scales (physical, role, social, emotional, cognitive), 3 symptom scales (fatigue, nausea/vomiting, pain), six single items, two global health and QOL items

Total items: 30

Trial data; Europe; newly diagnosed patients

(n = 504, 100% MM) [24]

(n = 708, 100% MM) [25]

(n = 274, 100% MM) [10]

(n = 524 at inclusion) (428 comp, 100% MM) [39, 49-51]

(n = 92, 100% MM) [44]

Trial data; US, Canada, Europe and Israel; relapsed

(n = 202, 100% MM) [21, 46]

(n = 598, 100% MM) [35]

HSCT patients; Europe and US

(n = 79, 58% MM) [22]

(n = 17, 29% MM) [26]

(n = 25, 28% MM) [27]

(n = 304, 37% MM) [28]

(n = 15, 100% MM) [30]

(n = 12, 100% MM) [45]

(n = 22, 55% MM) [47]

(n = 131, 28.2% MM) [31]

(n = 96, 58.3% MM) [23]

(n = 145, 40% MM) [16]

Mixed disease stages and treatments; Europe

(n = 60, 100% MM) [41]

(n = 132, 100% MM) [37]

(n = 239, 100% MM) [32-34]

Construct validity

All subscales shown to be impaired compared to population norms [25, 28, 37, 44, 47]. Some scales significantly improved with increasing time post-HSCT [28]. 67% and 43% scored below the 10th percentile for physical functioning and global QOL subscales [25]. Functional subscales and global QOL lower in MM than general haematology [37]. Pain, fatigue, physical and global QOL subscales able to discriminate those who improved vs. stable/deteriorated [34]. All subscales except single item diarrhoea discriminated between patients with different performance status and response status [49]. Significant differences in global QOL or global health status between treatment arms in trials [35, 41]. Scale structure verified, non-overlapping scales [39]

Criterion validity

No correlation of any subscale with the SEIQoL-Index (individual QOL scale with patient-nominated domains) suggesting independence [22]

Internal consistency

Conbach's α 0.54–0.89 for all subscales [26, 37, 39, 49] except 0.49 for social functioning in one group [26]

Responsiveness

Changes reported for all subscales over time, although statistical significance not always reported [10, 21, 23-28, 30, 32, 34, 35, 45, 47, 49, 50]. Some trials showed non-significant differences between baseline and follow-up, but not powered for overall HRQOL as primary outcome [31]. Statistically significant changes from baseline to follow-up shown in physical, role, global QOL and some symptom scales [16]

Global QOL scale had statistically significant standardised response means in patients who improved (SRM 0.32, P < 0.01) and deteriorated (SRM 0.57, P < 0.01, [33])

Floor and ceiling effects

Full range of possible scores observed for all scales at two time points (baseline and 6 months, [49]) Floor and ceiling effects small for global QOL scale – only a small number of patients achieved lowest or highest scores [33]

Predictive validity

Univariate analysis showed physical, role, social cognitive, fatigue, pain, global QOL and some single item scales were all related to survival [21, 46, 51]. Multivariate analyses showed mixed results in different groups, with no predictive domains [21]; physical and cognitive [51]; fatigue and physical [46]; or psychosocial domains predicting survival [44]

Minimal important difference

Mean score changes of approximately 6–17 important to patients [32]. Larger MID of 12–27 needed in patients who are deteriorating due to response shift [34]

An absolute change of 8–12 points in global QOL score (scale 0–100) was important to patients [33]

European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire – myeloma module (EORTC-QLQ-MY24, [19, 21, 43, 46])

For use only in conjunction with the EORTC-QLQ-C30.

Disease symptoms, treatment side effects, social support, future perspective

Total items: 24 (+30)

Trial data; Europe; 94% newly diagnosed patients (n = 240, 100% MM) [19]

Trial data; US; relapsed disease (n = 202, 100% MM) [21, 46]

Sweden, Denmark, UK and Germany; mixed disease stages (n = 116, 100% MM) [43]

Content validity

Literature search and informal interviews with oncologists, haematologists and patients generated 43 issues, subsequently reduced to 24 after further review and cognitive interviewing with patients [43]. In subsequent field testing, 10–18% of patients felt there were missing items [19]

Construct validity

Improvement in disease symptom subscale seen in those responding to treatment compared to non-responders (P = 0.02, [21]) Moderate correlations between global QOL scale of EORTC-QLQ-C30 and all subscales of MY24, except for social functioning, where no correlation seen [19]

Internal consistency

Cronbach's α 0.70–0.92 for all subscales [19]

Responsiveness

Improvement reported over time in disease symptoms and future perspectives subscales, but statistical significance not reported [21]

Predictive validity

In univariate analysis disease symptoms [21, 46], treatment side effects [21, 46] and social support [46] predicted survival, but not in multivariate analysis [21, 46]

European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire – myeloma module (EORTC-QLQ-MY20, [19, 37])

For use only in conjunction with the EORTC-QLQ-C30.

Disease symptoms, treatment side effects, future perspective, body image

Total items: 20 (+30)

Trial data; Europe; 94% newly diagnosed patients (n = 240, 100% MM) [19]

UK patients >1 year from diagnosis (n = 132, 100% MM) [37]

Content validity

Items as in MY24 module (described above) but social support subscale removed due to ceiling effect [19]

Construct validity

Poor PS at baseline showed significant decrease in disease symptoms, side effects and body image subscales (P < 0.003) and approached significance for future perspective (P = 0.065, [19])

Internal consistency

Cronbach's α 0.92 [37]

Responsiveness

Significant decreases over time in disease symptoms, side effects, and body image subscales (P < 0.005), and approaching significance (P = 0.06, [19])

Floor and ceiling effects

Some items skewed but full range of responses seen [19]

Predictive validity

Side effects single most important predictor for unmet supportive care needs (25% of variance explained, P < 0.001, [37])

European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire – high-dose chemotherapy

(EORTC-QLQ-HDC19, [16, 17])

For use only in conjunction with the EORTC-QLQ-C30.

Health worries, sexual functioning, joint and muscle pain, skin irritations

Total items: 19 (+30)

Swedish HSCT patients (n = 202, 28% MM) [17]

(n = 145, 40% MM) [16]

Construct validity

Differences in scores for lymphoma vs. patients with MM and CR vs. PR, but not for related donor vs. unrelated donor [17]

Criterion Validity

Changes in HDC-19 corresponded to changes in global QOL score of EORTC-QLQ–C30 (data not shown, [17])

Internal consistency

Cronbach's α >0.7 for sexual future health perspectives; low for joint and muscle pain and skin irritation [17]

Test-Retest Reliability

Strong correlation in scores from inclusion to baseline for all scales (range 0.96–1.00, [17])

Responsiveness

Most items responsive to change between baseline and 1 month post-HSCT [17]. Changes from baseline to 1 and 12 months post-HSCT were not significant for sexual functioning and future health perspectives [16]. Significance reached for changes in some symptom items from baseline to 1 and 12 months post-HSCT [16]

Floor and ceiling effects

Symptom scales highly skewed (floor effect). Functional scales less skewed, except sexual functioning [17]

Nil reported in studies meeting inclusion criteria

Functional Assessment of Cancer Therapy – anaemia questionnaire (FACT-An, [36, 38])

Consists of general QOL scale (FACT-G) plus fatigue and anaemia subscales

4 general QOL subscales (physical, social/family, emotional, functional) plus fatigue and anaemia subscales

Total items: 49

Trial data; Canada, Australia and Europe; haematological cancer and anaemia (n = 303, 49% MM) [36]

Trial data; Europe and Russia; mixed haematological cancer patients (n = 343 at inclusion, 34%MM) [38]

Construct validity

Statistically significant difference in total scores between responders to Epoetin and non-responders at 9, 12 and 16 weeks (P < 0.05, [38]). Clinically meaningful improvements in fatigue were associated with improved QOL scores (P < 0.001 for total scores and all subscales except social functioning, P = 0.148, [36])

Nil reported in studies meeting inclusion criteria

Responsiveness

Increase in total scores from baseline to 12 weeks [36] and 16 weeks [38], although statistical significance not reported.

Nil reported in studies meeting inclusion criteria

Functional Assessment of Cancer Therapy – bone marrow transplant questionnaire (FACT-BMT, [11, 20, 29])

Consists of general QOL scale (FACT-G) plus bone marrow transplant subscale.

4 general QOL subscales (physical, social/family, emotional, functional) plus bone marrow transplant subscale

Total items: 50

Spanish HSCT patients (n = 70, 26%MM) – NB used modified FACT-BMT with 5 additional questions for graft versus host disease [20]

Japanese HSCT patients (n = 36, 44% MM) [29]

US HSCT patients (n = 94, 100% MM) [11]

Construct validity

38.7% of patients greater than one SD worse than population norms [11]

Criterion validity

Total scores FACT-BMT well correlated with SF-36 (r = 0.53, [29])

Internal consistency

Cronbach's α 0.74–0.90 over 2 assessments [11], and >0.77 in all subscales [29]

Responsiveness

Significant deterioration on BMT subscale from stem cell collection to immediate post-transplant period (P < 0.05), but effect sizes small (0.23–0.34, [11])

Improvements seen in physical well-being items from HSCT to 1 year post (statistical significance not reported, other subscales not reported, [20])

Nil reported in studies meeting inclusion criteria
Short Form-36 (SF-36, [18, 29, 48])

Physical function, physical health, bodily pain, general mental health, social function, role/emotional, vitality, general health

Total items: 36

Trial data; UK HSCT patients (n = 58, 33% MM) [18]

Japanese HSCT patients (n = 36, 44% MM) [29]

US HSCT patients (n = 17, 47% MM) [48]

Construct validity

Lower mean SF-36 scores compared to population norms 6 months post-HSCT, statistical significance not reported [18]

Criterion Validity

Total scores SF-36 well correlated with FACT-BMT (r = 0.53, [29])

Internal consistency

Cronbach's α ≥0.7 in all domains [29]

Responsiveness

Statistically significant improvements for SF-36 physical and role functioning over study period of 12 weeks [48]

Nil reported in studies meeting inclusion criteria
Short Form-12 (SF-12, [3, 40])

Physical functioning, mental health functioning

Total items: 12

US patients undergoing evaluation for HSCT (n = 213, 100% MM) [3]

US patients receiving HSCT (n = 61, 100% MM) [40]

Construct validity

53% and 22% participants worse than general population in physical and mental summary scores, respectively [40]

60% and 28% participants worse than general population in physical and mental summary scores, respectively [3]

Nil reported in studies meeting inclusion criteriaNil reported in studies meeting inclusion criteriaNil reported in studies meeting inclusion criteria
Schedule for Evaluation of Individual Quality of Life – direct weighting (SEIQoL-DW, [22, 47])

5 ‘cues’ important to QOL are nominated by respondent. Each cue scored giving SEIQoL-Index score and relative importance weighted. Also 0–100 SEIQoL-VAS score of overall QOL

Total items: 5 + VAS

German HSCT patients (n = 79, 58% MM) [22]

Swedish HSCT patients (n = 22, 55% MM) [47]

Construct validity

Moderate correlation between SEIQoL-Index and the SEIQoL-VAS (0.42, [22]). SEIQoL-Index significantly different to reference population prior to HSCT but no difference post [47]

Criterion validity

No correlation between SEIQoL-Index and EORTC-QLQ-C30 symptom scales. SEIQoL-VAS weakly correlated with some subscales of EORTC-QLQ-C30 [22]

Nil reported in studies meeting inclusion criteria

Responsiveness

Significant change in SEIQoL-Index before and 1 year post-HSCT [47]

Nil reported in studies meeting inclusion criteria
EuroQol-5D (EQ-5D, [33, 45])

Mobility, self care, usual activities, pain/discomfort, anxiety/depression

Total items: 5

Dutch HSCT patients (n = 12, 100% MM) [45]

Mixed disease stages and treatments; Norway

(n = 239, 100% MM) [33]

Nil reported in studies meeting inclusion criteriaNil reported in studies meeting inclusion criteria

Responsiveness

Increase in mean utility from 1 to 12 months postdischarge approached significance (P = 0.06, [45])

Statistically significant standardised response means in patients who improved (SRM 0.43, P < 0.01) and deteriorated (SRM 0.45, P < 0.01, [33])

An absolute change of 0.08–0.10 points (scale 0–1) was important to patients [33]
15-Dimension (15D, [33])

Breathing, mental function, communication, vision, mobility, usual activities, hearing, eating, eliminating, sleeping, distress,

discomfort/symptoms, depression, vitality, and sexual activity

Total items: 15

Mixed disease stages and treatments; Norway (n = 239, 100% MM) [33]Nil reported in studies meeting inclusion criteriaNil reported in studies meeting inclusion criteria

Responsiveness

Statistically significant standardised response mean in patients who improved (SRM 0.37, P < 0.01), but not significant in those who deteriorated (SRM 0.23, P = 0.27, [33])

An absolute change of 0.02–0.03 points (scale 0–1) was important to patients [33]
Life ingredient profile (LIP, [42])

3 parts: LIP1 – physical and mental state before illness; LIP2 – mobility and autonomy, physical symptoms, mental symptoms, treatment side effects, disease symptoms; LIP3 – ability to enjoy leisure activities

Total items: 22 + 22 + 8

Swedish haematological cancer patients (n = 35, 29% MM) [42]

Content validity

Preliminary version reviewed with patients and staff. Revised questionnaire discussed with expert group [42]

Construct validity

LIP 2 + 3 scores different between advanced patients with MM and total MM group. LIP2 + 3 scores different between time points (induction and discharge)

Criterion validity

Correlation >0.7 between LIP2 and two other measures (KPS and Vitagram)

Internal consistency

Cronbach's α 0.72–0.77 for LIP2 and 0.29–0.68 for LIP3 [42]

Test-retest reliability

Kappa coefficient 0.42–1.00 for all questions in LIP 2 or LIP 3; low kappa for fatigue (0.43), nausea (0.52), eating (0.52) and appetite (0.44, [42])

Responsiveness

Limited data. Longitudinal LIP2 scores for a single patient with myeloma presented at 7 time points over 18 weeks showing changes in physical symptoms, mental symptoms and mobility/autonomy in the terminal phase [42]

Nil reported in studies meeting inclusion criteria
Quality of Life Index (QLI, [26])

Health and functioning, social and economic, psychological and spiritual, family

Total items: 70

US HSCT patients (n = 17, 29% MM) [26]Nil reported in studies meeting inclusion criteria

Internal consistency

Cronbach's α adequate for total QLI (0.87) and health and functioning (0.77), social and economic (0.71), psychological and spiritual subscales (0.77), low for family subscale (0.18, [26])

Responsiveness

No statistically significant differences before and after HSCT for total QLI, health and functioning, social and economic and psychological or spiritual subscales [26]

Clinical important difference

A decline of 3.68 points on health and functioning subscales suggested clinically important difference [26]

Most studies reported traditional psychometric properties (validity, reliability and responsiveness) with fewer reports of more clinically applicable properties such as prognostic power (Table 5).

The majority of samples used for validation were taken from European or North American populations, and many were making use of HRQOL data collected during chemotherapy trials, or in groups undergoing stem cell transplantation. Relatively few samples were clinically representative (Table 5).

Content validity of HRQOL tools

The ability of each instrument to capture issues important to the HRQOL of patients is shown in Table 4. Some instruments are designed as modules to be used alongside a ‘core’ questionnaire (EORTC-QLQ-MY24, EORTC-QLQ-MY20 and EORTC-QLQ-HDC19 – all designed for use alongside the core EORTC-QLQ-C30). In such cases, the coverage was assessed for both the core questionnaire and module together (Table 4).

No single instrument covered all issues identified as important by people with myeloma. The most comprehensive coverage was found in the EORTC-QLQ-MY24 (myeloma-specific module, used in conjunction with core cancer questionnaire EORTC-QLQ-C30), the FACT-BMT and the QLI. The EORTC-QLQ-MY24 omits only the domains of libido/sexual function and the presence of support/coping mechanisms. Sexual function was considered in the development of the MY24, but only surfaced as a potential item in later stages during pilot testing, by which time the items had been selected. The authors comment that this is an area for further research [43]. The FACT-BMT omits items relating to social/participatory function and having the amount of myeloma-related information. The QLI omits specific items about social function and myeloma-related information – although related questions about employment, relationships with friends and general satisfaction with health care are included. This review identified one tool with no predefined questions and all domains nominated by the respondent (the SEIQoL-DW). This could not be evaluated in this way and so is excluded from Table 4. Arguably, the SEIQoL-DW best captures patients concerns as each respondent nominates domains individually. However, only the five most important ‘cues’ can be nominated by the respondent when using this tool.

Perceptions of health status vs. health evaluations

This assessment was carried out using the most current available version for each tool. The versions used in each case are shown in Table 4. No complete version of the EORTC-QLQ-HDC19 module or the LIP were available, and so the items within these tools were drawn from articles describing their development or use [42, 59, 60].

Most tools were found to primarily elicit perceptions of health status (Table 4). The tools developed by the FACT group elicit a more balanced mixture of health status and health evaluations. The QLI was the only tool to focus entirely on evaluations – by asking respondents only about their satisfaction with each issue, and their relative importance. Implications for the utility of each tool are discussed below.

Discussion

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Conflicts of interest
  8. References

Psychometric validation of HRQOL instruments in myeloma

This review identified 13 multidimensional HRQOL instruments validated to varying degrees in MM. The most extensive psychometric validation has occurred with the EORTC-QLQ-C30, followed by its myeloma-specific module (EORTC-QLQ-MY24, subsequently revised to the MY20, Table 5). Only these instruments have undergone comprehensive psychometric validation in samples composed purely of people with myeloma. Other instruments have undergone incomplete psychometric validation in patients with myeloma (EQ-5D, 15D) been developed or evaluated in mixed samples of >25% myeloma (EORTC-QLQ-HDC19, FACT-BMT, SEIQoL-DW, LIP) or simply been used in myeloma with some measurement properties reported (FACT-An, QLI, SF-36, SF-12, Table 2).

Content validity of HRQOL instruments for use in myeloma

This review identified only seven articles using inductive methods to explore issues related to the HRQOL of patients with myeloma. However, the included articles explored related concepts such as distress, unmet need and lived experience, rather than directly asking what is important to patients’ HRQOL. The literature lacks any attempt to directly and comprehensively characterise HRQOL in this group. Table 4 shows that even the most comprehensive tools do not capture all HRQOL domains important to patients, although the EORTC-QLQ-C30 plus MY24 do come close. This is supported by the fact that 10–18% of patients felt there were missing items in the MY24 [11]. The EORTC now recommends the MY20 as the preferred tool following removal of the social subscale of the MY24. This removed subscale addressed satisfaction with care, relationships with doctors and information needs – all of which were frequently reported as important to patients ([43, 52-57], Table 3). They were removed from the MY24 due to floor and ceiling effects [19], rather than the belief that they did not contribute to HRQOL.

It is also noteworthy that no correlation was found between any subscale of the EORTC-QLQ-C30 (core questionnaire) and the global score generated by the SEIQoL-DW [22]. This suggests that these two scales may be tapping into different latent variables and measuring different things. The EORTC-QLQ-C30 is psychometrically sound, but has been developed with a particular focus on symptoms. Lack of correlation with the SEIQoL-DW suggests that there may be additional or different issues important to QOL from the individual perspective. However, each tool has its strengths, and the choice of tool will depend on the context in which it is used. If a researcher wants to describe the incidence of side effects in a particular group, then information about the presence or absence of symptoms will be particularly relevant and the EORTC tools may be more appropriate. However, in clinical practice, we may want a tool to focus more on the particular concerns of each patient (such as the SEIQoL-DW). However, users should consider the practical difficulties of individualised tools such as the SEIQoL-DW, which are time-consuming, require specialised training, difficult to compare between studies and different interviewers, and can be less feasible in certain groups such as those with chronic disease or the elderly [61, 62].

An important application of HRQOL instruments is in the generation of quality adjusted life years (QALYs) for the allocation of healthcare resources. The EQ-5D is widely used for this purpose. Table 4 shows that the EQ-5D performed poorly in capturing all domains important to HRQOL in myeloma. However, it is important to acknowledge that such tools are used to compare health states between different diagnoses, and so cannot seek to capture disease-specific issues with such granularity. Therefore, it is perhaps unfair to judge them by the criteria presented here. However, these findings serve as a reminder to consider the intended utility when selecting a tool for a given purpose.

Samples used for validation – implications for use in different settings

The vast majority of psychometric validation has taken place in Europe and the United States (Table 5), and their application outside these places should be made with this in mind. Many participants used to validate HRQOL instruments were awaiting/undergoing stem cell transplant or recruited into trials of other intensive chemotherapy treatments (Table 5). The tendency to validate instruments in patients receiving active treatment is perhaps not surprising because their use is common in trials and so large data sets exist. Moreover, many instruments have been designed specifically for use in research, and this is reflected in their content and design. For example, the items for the EORTC-QLQ-MY24 were generated with specific emphasis on treatment side effects [43], and so the resulting tool has specific relevance during periods of intensive treatment. But the advent of novel agents has meant that many treatment regimens no longer use intensive chemotherapy, and few HRQOL tools have been developed and validated for use in this group.

The preponderance of validation in those receiving intensive treatment also creates a bias towards patients who are medically fitter and usually younger. The HRQOL of these patients is likely to be more affected by disease symptoms and treatment side effects than those off treatment, for whom future perspectives and fear of relapse may be more of a concern. Similarly, higher numbers of people with newly diagnosed disease were used to validate the EORTC-QLQ-C30 than those after relapse. It is possible that the domains of HRQOL important to people at later stages of disease would differ from those at diagnosis. This is supported by a study investigating minimal important difference and response shift in the EORTC-QLQ-C30, which found evidence not only that response shift exists in myeloma, but the magnitude and direction varied between those who clinically improved and those who deteriorated [34]. What is important to HRQOL may therefore be different at later disease stages. Although this requires further exploration, it should be borne in mind when using existing HRQOL tools in this setting because most of their validation has occurred earlier in the disease trajectory. It is a significant and novel finding of this review that no instruments were identified that have been validated specifically for use in the palliative phase of myeloma or as an adjunct to clinical care.

Health status vs. health evaluations – implications for use in different settings

Table 4 shows that many of the tools identified tended to elicit perceptions of health status, with a minority focussing on health evaluations. Questions about health status ask the respondent to assess only the presence or severity of a problem, but give no information about the impact of the problem on their life. By contrast, health evaluations require the respondent to first judge the degree of the problem and also evaluate its impact.

The status/evaluation distinction has been described by Ferrans [14] and may affect the suitability of a tool for a given purpose. For example, the role of HRQOL assessment in a drug trial is ultimately to detect differences between treatment arms. Questions about health status may be more effective in detecting these differences as they are less susceptible to change with variations in external factors such as employment status, relationships with caregivers etc [63]. Such external and environmental factors are of less interest in the trial setting.

By contrast, the role of HRQOL assessment in clinical practice is ultimately to improve HRQOL, and help flag and prioritise the most important problems from the patient's perspective [6]. So it is perhaps of greater importance to capture patient's evaluation of their health to achieve these ends. For example, a patient may be asked ‘What is your current level of pain from 1 to 10?’ (health status) and report a score of 2/10. The same patient may be asked ‘How much does pain currently interfere with your life from 1 to 10?’ (health evaluation) and report a score of 9/10 because even a small amount of pain prevents them from working. Clinicians and researchers should always consider this distinction when selecting a tool for a given purpose, as the choice of tools should ultimately be guided by its intended utility.

The QLI questionnaire appeared reasonably comprehensive to the issues important to patients and was the only tool to mainly elicit patients’ evaluation of their health, as apposed to health status. This may make it better suited to certain clinical applications, although this should be read with caution because its psychometric validation in myeloma remains limited.

Recommendations for future research

Existing tools have been predominantly developed and validated in patients receiving intensive treatment, and validation in clinically representative groups would be of value. There is a particular lack of work looking at the palliative phase, where the validation of existing palliative tools may be more appropriate. Further exploration of the changing internal values of patients as they pass through different disease stages (so-called response shift) may cast light on how HRQOL tools could be designed to function throughout the whole illness trajectory. Existing tools tend to be designed for use in research settings, and their adaptation or the development of new tools specifically for use in clinical practice would be beneficial. There is also a need for more inductive qualitative research to better characterise the meaning and issues important to HRQOL from the patients’ perspective.

Limitations of this review

The summary list of HRQOL issues used to assess content validity (Table 5) is based on a small body of literature and was compiled subjectively. Different researchers may have arrived at a different list. The literature summarised in Table 4 arguably does not capture all HRQOL issues important to patients. Few of the qualitative studies directly address HRQOL, but instead focus on related issues such as trauma and post-traumatic growth; illness experience and unmet needs; and distressing experiences. However, closely related – there is a conceptual distinction between these issues and HRQOL. They were included in the review because it is reasonable to assume that distress/trauma/unmet needs will generate closely related issues, but this paucity of inductive research into HRQOL in myeloma casts doubt on whether content validity can be adequately assessed with this method. Is it also possible that our search strategy was not able to capture all relevant studies.

Conclusions

We have an ageing population in the UK and the burden of disease is increasing. Myeloma is being transformed from a disease that you died from to a disease that you live with, making it important to recognise issues of quality of life looking into the future. The emphasis of the studies identified in this review has been to develop and validate HRQOL tools for use in research settings. The EORTC-QLQ-C30 and its myeloma modules (MY20 and MY24) are the most comprehensively validated instruments for this purpose. These tools are generally reliable, valid and responsive in the trial setting, although are less well validated in clinically representative groups. The EORTC now recommends the use of the MY20 module (above the MY24), although this may miss some psychosocial and care-related issues important to patients. There is a need for more research to identify the issues important to the HRQOL of patients with myeloma across all disease stages, and the development of new tools specifically for use in the clinical care of patients with myeloma is a worthwhile direction for future research.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Conflicts of interest
  8. References

This work was supported by grants from Myeloma UK and King's College Hospital NHS Trust. These organisations were not involved in planning the study or preparing the manuscript.

References

  1. Top of page
  2. Abstract
  3. Methods
  4. Results
  5. Discussion
  6. Acknowledgements
  7. Conflicts of interest
  8. References
  • 1
    Cancer Research UK Incidence Statistics(June 2011). http://infocancerresearchukorg/cancerstats/reports/
  • 2
    Sirohi B, Powles R. Epidemiology and outcomes research for MGUS, myeloma and amyloidosis. Eur J Cancer 2006;42:167183.
  • 3
    Sherman AC. Psychosocial adjustment and quality of life among multiple myeloma patients undergoing evaluation for autologous stem cell transplantation. Bone Marrow Transplant 2004;33:95562.
  • 4
    Johnsen AT, Tholstrup D, Petersen MA, Pedersen L, Groenvold M. Health related quality of life in a nationally representative sample of haematological patients. Eur J Haematol 2009;83:13948.
  • 5
    Kvam AK, Fayers P, Hjermstad M, Gulbrandsen N, Wisloff F. Health-related quality of life assessment in randomised controlled trials in multiple myeloma: a critical review of methodology and impact on treatment recommendations. Eur J Haematol 2009;83:27989.
  • 6
    Higginson I, Carr A. Using quality of life measures in the clinical setting. Br Med J 2001;322:1297300.
  • 7
    Bausewein C, Simon ST, Benalia H, Downing J, Mwangi-Powell FN, Daveson BA, Harding R, Higginson IJ. Implementing patient reported outcome measures (PROMs) in palliative care – users’ cry for help. Health Qual Life Outcomes 2011;9:111.
  • 8
    Greenhalgh J. The applications of PROs in clinical practice: what are they, do they work, and why? Qual Life Res 2009;18:11523.
  • 9
    Velikova G, Booth L, Smith AB, Brown PM, Lynch P, Brown JM, Selby PJ. Measuring quality of life in routine oncology practice improves communication and patient well-being: a randomized controlled trial. J Clin Oncol 2004;22:71424.
  • 10
    Gulbrandsen N, Wisloff F, Brinch L, et al. Health-related quality of life in multiple myeloma patients receiving high-dose chemotherapy with autologous blood stem-cell support. Med Oncol 2001;18:6577.
  • 11
    Sherman AC, Simonton S, Latif U, Plante TG, Anaissie EJ. Changes in quality-of-life and psychosocial adjustment among multiple myeloma patients treated with high-dose melphalan and autologous stem cell transplantation. Biol Blood Marrow Transplant 2009;15:1220.
  • 12
    Gruenewald DA, Higginson IJ, Vivat B, Edmonds P, Burman RE. Quality of life measures for the palliative care of people severely affected by multiple sclerosis: a systematic review. Mult Scler 2004;10:690704.
  • 13
    WHOQOL-Group. The World Health Organization quality of life assessment (WHOQOL): position paper from the World Health Organization. Soc Sci Med 1995;41:14039.
  • 14
    Ferrans CE. Definitions and conceptual models of quality of life. In: Lipscomb J, Gotay CC, Snyder C, eds. Outcomes Assessment in Cancer. Cambridge: Cambridge University Press; 2004:1430.
  • 15
    Hawker S, Payne S, Kerr C, Hardey M, Powell J. Appraising the evidence: reviewing disparate data systematically. Qual Health Res 2002;12:128499.
  • 16
    Andersson I, Ahlberg K, Stockelberg D. Patients’ perceptions of health-related quality of life during the first year after autologous and allogeneic stem cell transplantation. Eur J Cancer Care (Engl) 2011;20:36879.
  • 17
    Andersson I, Hjermstad M, Stockelberg D, Persson LO. Health related quality of life in stem cell transplantation: clinical and psychometric validation of the questionnaire module, high dose chemotherapy (HDC-19). Acta Oncol 2008;47:27586.
  • 18
    Bird L, Arthur A, Niblock T, Stone R, Watson L, Cox K. Rehabilitation programme after stem cell transplantation: randomized controlled trial. J Adv Nurs 2010;66:60716.
  • 19
    Cocks K, Cohen D, Wisloff F, et al. An international field study of the reliability and validity of a disease-specific questionnaire module (the QLQ-MY20) in assessing the quality of life of patients with multiple myeloma. Eur J Cancer 2007;43:16709.
  • 20
    Diez-Campelo M, Perez-Simon JA, Gonzalez-Porras JR, Garcia-Cecilia JM, Salinero M, Caballero MD, Canizo MC, Ocio EM, San Miguel JF. Quality of life assessment in patients undergoing reduced intensity conditioning allogeneic as compared to autologous transplantation: results of a prospective study. Bone Marrow Transplant 2004;34:72938.
  • 21
    Dubois D. Descriptive and prognostic value of patient-reported outcomes: the bortezomib experience in relapsed and refractory multiple myeloma. J Clin Oncol 2006;24:97682.
  • 22
    Frick E, Borasio GD, Zehentner H, Fischer N, Bumeder I. Individual quality of life of patients undergoing autologous peripheral blood stem cell transplantation. Psychooncology 2004;13:11625.
  • 23
    Frodin U, Borjeson S, Lyth J, Lotfi K. A prospective evaluation of patients' health-related quality of life during auto-SCT: a 3-year follow-up. Bone Marrow Transplant 2011;46:134552.
  • 24
    Gimsing P, Carlson K, Turesson I, et al. Effect of pamidronate 30 mg versus 90 mg on physical function in patients with newly diagnosed multiple myeloma (Nordic Myeloma Study Group): a double-blind, randomised controlled trial. Lancet Oncol 2010;11:97382.
  • 25
    Gulbrandsen N, Hjermstad MJ, Wisloff F, Nordic Myeloma Study G. Interpretation of quality of life scores in multiple myeloma by comparison with a reference population and assessment of the clinical importance of score differences. Eur J Haematol 2004;72:17280.
  • 26
    Hacker E, Ferrans C, Verlen E. Fatigue and physical activity in patients undergoing hematopoietic stem cell transplant. Oncol Nurs Forum 2006;33:61424.
  • 27
    Harder H, Duivenvoorden HJ, van Gool AR, Cornelissen JJ, van den Bent MJ. Neurocognitive functions and quality of life in haematological patients receiving haematopoietic stem cell grafts: a one-year follow-up pilot study. J Clin Exp Neuropsychol 2006;28:28393.
  • 28
    Hensel M, Egerer G, Schneeweiss A, Goldschmidt H, Ho AD. Quality of life and rehabilitation in social and professional life after autologous stem cell transplantation. Ann Oncol 2002;13:20917.
  • 29
    Imataki O, Nakajima K, Inoue N, Tamai Y, Kawakami K. Evaluation of QOL for stem cell transplantation recipients by SF-36 and FACT-BMT: preliminary results of FACT-BMT for Japanese patients. Gan To Kagaku Ryoho 2010;37:84751.
  • 30
    Iversen PO, Wisloff F, Gulbrandsen N. Reduced nutritional status among multiple myeloma patients during treatment with high-dose chemotherapy and autologous stem cell support. Clin Nutr 2010;29:48891.
  • 31
    Knols RH, De Bruin ED, Uebelhart D, Aufdemkampe G, Schanz U, Stenner-Liewen F, Hitz F, Taverna C, Aaronson NK. Effects of an outpatient physical exercise program on hematopoietic stem-cell transplantation recipients: a randomized clinical trial. Bone Marrow Transplant 2011;46:124555.
  • 32
    Kvam AK, Fayers P, Wisloff F. What changes in health-related quality of life matter to multiple myeloma patients? A prospective study Eur J Haematol 2010;84:34553.
  • 33
    Kvam AK, Fayers PM, Wisloff F. Responsiveness and minimal important score differences in quality-of-life questionnaires: a comparison of the EORTC QLQ-C30 cancer-specific questionnaire to the generic utility questionnaires EQ-5D and 15D in patients with multiple myeloma. Eur J Haematol 2011;87:3307.
  • 34
    Kvam AK, Wisloff F, Fayers PM. Minimal important differences and response shift in health-related quality of life; a longitudinal study in patients with multiple myeloma. Health Qual Life Outcomes 2010;8:79.
  • 35
    Lee SJ, Richardson PG, Sonneveld P, et al. Bortezomib is associated with better health-related quality of life than high-dose dexamethasone in patients with relapsed multiple myeloma: results from the APEX study. Br J Haematol 2008;143:5119.
  • 36
    Littlewood TJ, Kallich JD, San Miguel J, Hendricks L, Hedenus M. Efficacy of darbepoetin alfa in alleviating fatigue and the effect of fatigue on quality of life in anemic patients with lymphoproliferative malignancies. J Pain Symptom Manage 2006;31:31726.
  • 37
    Molassiotis A, Wilson B, Blair S, Howe T, Cavet J. Unmet supportive care needs, psychological well-being and quality of life in patients living with multiple myeloma and their partners. Psychooncology 2011;20:8897.
  • 38
    Osterborg A, Brandberg Y, Molostova V, Iosava G, Abdulkadyrov K, Hedenus M, Messinger D. Randomized, double-blind, placebo-controlled trial of recombinant human erythropoietin, epoetin beta, in hematologic malignancies. J Clin Oncol 2002;20:248694.
  • 39
    Ringdal K, Ringdal GI, Kaasa S, Bjordal K, Wisloff F, Sundstrom S, Hjermstad MJ. Assessing the consistency of psychometric properties of the HRQoL scales within the EORTC QLQ-C30 across populations by means of the Mokken Scaling Model. Qual Life Res 1999;8:2543.
  • 40
    Sherman AC, Coleman EA, Griffith K, Simonton S, Hine RJ, Cromer J, Latif U, Farley H, Garcia R, Anaissie EJ. Use of a supportive care team for screening and preemptive intervention among multiple myeloma patients receiving stem cell transplantation. Support Care Cancer 2003;11:56874.
  • 41
    Sirohi B, Powles R, Lawrence D, Treleaven J, Kulkarni S, Leary A, Rudin C, Horton C, Morgan G. An open, randomized, controlled, phase II, single centre, two-period cross-over study to compare the quality of life and toxicity experienced on PEG interferon with interferon-alpha2b in patients with multiple myeloma maintained on a steady dose of interferon-alpha2b. Ann Oncol 2007;18:138894.
  • 42
    Stalfelt AM, Wadman B. Assessing quality of life in leukemia: presentation of an instrument for assessing quality of life in patients with blood malignancies. Qual Assur Health Care 1993;5:20111.
  • 43
    Stead ML, Brown JM, Velikova G, Kaasa S, Wisloff F, Child JA, Hippe E, Hjorth M, Sezer O, Selby P. Development of an EORTC questionnaire module to be used in health-related quality-of-life assessment for patients with multiple myeloma. European Organization for Research and Treatment of Cancer Study Group on Quality of Life. Br J Haematol 1999;104:60511.
  • 44
    Strasser-Weippl K, Ludwig H. Psychosocial QOL is an independent predictor of overall survival in newly diagnosed patients with multiple myeloma. Eur J Haematol 2008;81:3749.
  • 45
    Uyl-de Groot CA, Buijt I, Gloudemans IJM, Ossenkoppele GJ, Berg HP, Huijgens PC. Health related quality of life in patients with multiple myeloma undergoing a double transplantation. Eur J Haematol 2005;74:13643.
  • 46
    Viala M, Bhakar AL, La Loge C, van de Velde H, Esseltine D, Chang M, Dhawan R, Dubois D. Patient-reported outcomes helped predict survival in multiple myeloma using partial least squares analysis. J Clin Epidemiol 2007;60:6709.e3.
  • 47
    Wettergren L, Sprangers M, Björkholm M, Langius-Eklöf A. Quality of life before and one year following stem cell transplantation using an individualized and a standardized instrument. Psychooncology 2008;17:33847.
  • 48
    Wilson RW, Jacobsen PB, Fields KK. Pilot study of a home-based aerobic exercise program for sedentary cancer survivors treated with hematopoietic stem cell transplantation. Bone Marrow Transplant 2005;35:7217.
  • 49
    Wisloff F, Eika S, Hippe E, Hjorth M, Holmberg E, Kaasa S, Palva I, Westin J. Measurement of health-related quality of life in multiple myeloma. Nordic Myeloma Study Group. Br J Haematol 1996;92:60413.
  • 50
    Wisloff F, Gulbrandsen N, Hjorth M, Lenhoff S, Fayers P. Quality of life may be affected more by disease parameters and response to therapy than by haemoglobin changes. Eur J Haematol 2005;75:2938.
  • 51
    Wisloff F, Hjorth M. Health-related quality of life assessed before and during chemotherapy predicts for survival in multiple myeloma. Nordic Myeloma Study Group. Br J Haematol 1997;97:2937.
  • 52
    Dahan JF, Auerbach CF. A qualitative study of the trauma and posttraumatic growth of multiple myeloma patients treated with peripheral blood stem cell transplant. Palliat Support Care 2006;4:36587.
  • 53
    Vlossak D, Fitch M. Multiple myeloma: the patient's perspecive. Can Oncol Nurs J 2008;18:14151.
  • 54
    Molassiotis A, Wilson B, Blair S, Howe T, Cavet J. Living with multiple myeloma: experiences of patients and their informal caregivers. Support Care Cancer 2011;19:10111.
  • 55
    Potrata B, Cavet J, Blair S, Howe T, Molassiotis A. Understanding distress and distressing experiences in patients living with multiple myeloma: an exploratory study. Psychooncology 2011;20:12734.
  • 56
    Maher K, De Vries K. An exploration of the lived experiences of individuals with relapsed Multiple Myeloma. Eur J Cancer Care (Engl) 2011;20:26775.
  • 57
    Kelly M, Dowling M. Patients' lived experience of myeloma. Nurs Stand 2011;25:3844.
  • 58
    Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009;151:2649.
  • 59
    Hjermstad M, Holte H, Evensen S, Fayers P, Kaasa S. Do patients who are treated with stem cell transplantation have a health-related quality of life comparable to the general population after 1 year? Bone Marrow Transplant 1999;24:9118.
  • 60
    Stalfelt AM, Zettervall O. Quality of life in young patients with chronic myelocytic leukaemia during intensive treatment including interferon. Leuk Res 1997;21:77583.
  • 61
    Farquhar M, Ewing G, Higginson IJ, Booth S. The experience of using the SEIQoL-DW with patients with advanced chronic obstructive pulmonary disease (COPD): issues of process and outcome. Qual Life Res 2010;19:61929.
  • 62
    Hall S, Opio D, Dodd RH, Higginson IJ. Assessing quality-of-life in older people in care homes. Age Ageing 2011;15.
  • 63
    Gotay CC. Trial-related quality of life: using quality of life assessment to distinguish among cancer therapies. J Nat Cancer Inst Monogr 1996;20:16.
  • 64
    Streiner D, Norman G. Criterion Validation in Health measurement Scales: a Practical Guide to Their Developement and Use, 4th edn. Oxford: Oxford Medical Publications, 2008:254.