The EORTC QLU-C10D is a valid cancer-specific preference-based measure for cost-utility and health technology assessment in the Netherlands.

BACKGROUND: Cost-utility analysis typically relies on preference-based measures (PBMs). While generic PBMs are widely used, disease-specific PBMs can capture aspects relevant for certain patient populations. Here the EORTC QLU-C10D, a cancer-specific PBM based on the QLQ-C30, is validated using Dutch trial data with the EQ-5D-3L as a generic comparator measure. METHODS: We retrospectively analysed data from four Dutch randomised controlled trials (RCTs) comprising the EORTC QLQ-C30 and the EQ-5D-3L. Respective Dutch value sets were applied. Correlations between the instruments were calculated for domains and index scores. Bland-Altman plots and intra-class correlations (ICC) displayed agreement between the measures. Independent and paired t-tests, effect sizes and relative validity indices were used to determine the instruments' performance in detecting clinically known-group differences and health changes over time. RESULTS: We analysed data from 602 cancer patients from four different trials. In overall, the EORTC QLU-C10D showed good relative validity with the EQ-5D-3L as a comparator (correlations of index scores r = 0.53-0.75, ICCs 0.686-0.808, conceptually similar domains showed higher correlations than dissimilar domains). Most importantly, it detected 63% of expected clinical group differences and 50% of changes over time in patients undergoing treatment. Both instruments showed poor performance in survivors. Detection rate and measurement efficiency were clearly higher for the QLU-C10D than for the EQ-5D-3L. CONCLUSIONS: The Dutch EORTC QLU-C10D showed good comparative validity in patients undergoing treatment. Our results underline the benefit that can be achieved by using a cancer-specific PBM for generating health utilities for cancer patients from a measurement perspective.

Hidden in plain sight - Survival consequences of baseline symptom burden in women with recurrent ovarian cancer.

OBJECTIVE: To describe the baseline symptom burden(SB) experienced by patients(pts) with recurrent ovarian cancer(ROC) prior and associations with progression free survival (PFS) and overall survival (OS). METHODS: We analysed baseline SB reported by pts. with platinum resistant/refractory ROC (PRR-ROC) or potentially­platinum sensitive ROC receiving their third or greater line of chemotherapy (PPS-ROC≥3) enrolled in the Gynecologic Cancer InterGroup - Symptom Benefit Study (GCIG-SBS) using the Measure of Ovarian Symptoms and Treatment concerns (MOST). The severity of baseline symptoms was correlated with PFS and OS. RESULTS: The 948 pts. reported substantial baseline SB. Almost 80% reported mild to severe pain, and 75% abdominal symptoms. Shortness of breath was reported by 60% and 90% reported fatigue. About 50% reported moderate to severe anxiety, and 35% moderate to severe depression. Most (89%) reported 1 or more symptoms as moderate or severe, 59% scored 6 or more symptoms moderate or severe, and 46% scored 9 or more symptoms as moderate or severe. Higher SB was associated with significantly shortened PFS and OS; five symptoms had OS hazard ratios larger than 2 for both moderate and severe symptom cut-offs (trouble eating, vomiting, indigestion, loss of appetite, and nausea; p < 0.001). CONCLUSION: Pts with ROC reported high SB prior to starting palliative chemotherapy, similar among PRR-ROC and PPS-ROC≥3. High SB was strongly associated with early progression and death. SB should be actively managed and used to stratify patients in clinical trials. Clinical trials should measure and report symptom burden and the impact of treatment on symptom control.

Danish value sets for the EORTC QLU-C10D utility instrument.

PURPOSE: In this study, we developed Danish utility weights for the European Organisation for Research and Treatment of Cancer (EORTC) QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30. METHODS: Following a standardized methodology, 1001 adult participants from the Danish general population were quota-sampled and completed a cross-sectional web-based survey and discrete choice experiment (DCE). In the DCE, participants considered 16 choice sets constructed from the key 10 dimensions of the QLU-C10D and chose their preferred health state for each one. Utility weights were calculated using conditional logistic regression with correction for non-monotonicity. RESULTS: The sample (n = 1001) was representative of the Danish general population with regard to age and gender. The domains with the largest utility decrements, i.e., the domains with the biggest impact on health utility, were physical functioning (- 0.224), pain (- 0.160), and role functioning (- 0.136). The smallest utility decrements were observed for the domains lack of appetite (- 0.024), sleep disorders (- 0.057), and fatigue (- 0.064). Non-monotonicity of severity levels was observed for the domains sleep disturbances, lack of appetite, and bowel problems. Deviations from monotonicity were not statistically significant. CONCLUSION: The EORTC QLU-C10D is a relatively new multi-attribute utility instrument and is a promising cancer-specific health technology assessment candidate measure. The country-specific Danish utility weights from this study can be used for cost-utility analyses in Danish patients and for comparison with other country-specific utility data.

United States Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument.

OBJECTIVES: To develop a value set reflecting the United States (US) general population's preferences for health states described by the Functional Assessment of Cancer Therapy (FACT) eight-dimensions preference-based multi-attribute utility instrument (FACT-8D), derived from the FACT-General cancer-specific health-related quality-of-life (HRQL) questionnaire. METHODS: A US online panel was quota-sampled to achieve a general population sample representative by sex, age (≥ 18 years), race and ethnicity. A discrete choice experiment (DCE) was used to value health states. The valuation task involved choosing between pairs of health states (choice-sets) described by varying levels of the FACT-8D HRQL dimensions and survival (life-years). The DCE included 100 choice-sets; each respondent was randomly allocated 16 choice-sets. Data were analysed using conditional logit regression parameterized to fit the quality-adjusted life-year framework, weighted for sociodemographic variables that were non-representative of the US general population. Preference weights were calculated as the ratio of HRQL-level coefficients to the survival coefficient. RESULTS: 2562 panel members opted in, 2462 (96%) completed at least one choice-set and 2357 (92%) completed 16 choice-sets. Pain and nausea were associated with the largest utility weights, work and sleep had more moderate utility weights, and sadness, worry and support had the smallest utility weights. Within dimensions, more severe HRQL levels were generally associated with larger weights. A preference-weighting algorithm to estimate US utilities from responses to the FACT-General questionnaire was generated. The worst health state's value was -0.33. CONCLUSIONS: This value set provides US population utilities for health states defined by the FACT-8D for use in evaluating oncology treatments.

Integrated Geriatric Assessment and Treatment Effectiveness (INTEGERATE) in older people with cancer starting systemic anticancer treatment in Australia: a multicentre, open-label, randomised controlled trial.

BACKGROUND: The effectiveness of comprehensive geriatric assessment (CGA) in improving health outcomes in cancer settings is unclear. We evaluated whether CGA can improve health-related quality of life (HRQOL) in older people with cancer who are starting systemic anticancer treatment. METHODS: INTEGERATE is a multicentre, open-label, pragmatic, parallel-group, randomised controlled trial that was done at three hospitals in Australia. Participants aged 70 years and older with solid cancer or diffuse large B-cell lymphoma planned for chemotherapy, targeted therapy, or immunotherapy, were randomly assigned (1:1; using a central computer-generated minimisation algorithm with a random element, balancing treatment intent, cancer type, age, sex, and performance status) to receive CGA integrated into oncology care (integrated oncogeriatric care) or usual care only. Group assignment was not concealed from the participants and clinicians. The primary outcome was HRQOL over 24 weeks, assessed at baseline, week 12, week 18, and week 24, using the Elderly Functional Index (ELFI; score range 0-100). Analyses were by intention to treat. The trial is registered with ANZCTR.org.au, ACTRN12614000399695, and is completed. FINDINGS: Between Aug 18, 2014, and Sept 5, 2018, 154 participants were randomly assigned to integrated oncogeriatric care (n=76) or usual care (n=78). 13 participants died by week 12 and 130 (92%) of the remaining 141 participants completed two or more ELFI assessments. Participants assigned to integrated oncogeriatric care reported better adjusted ELFI change scores over 24 weeks compared with those in the usual care group (overall main effect of group: t=2·1, df=213, p=0·039; effect size=0·38), with maximal between-group differences at week 18 (mean difference in change 9·8 [95% CI 2·4-17·2]; p=0·010, corrected p=0·030, effect size=0·48). The integrated oncogeriatric care group also had significantly fewer unplanned hospital admissions at 24 weeks (multivariable-adjusted incidence rate ratio 0·60 [95% CI 0·42-0·87]; p=0·0066). No statistically significant between-group difference was observed in overall survival. INTERPRETATION: CGA led to better quality of life and health-care delivery in older people receiving systemic anticancer treatment. Routine CGA-based interventions should be considered in at-risk older people starting systemic anticancer treatment. FUNDING: National Health and Medical Research Council (Australia), Monash University, and Eastern Health.

The FACT-8D, a new cancer-specific utility algorithm based on the Functional Assessment of Cancer Therapies-General (FACT-G): a Canadian valuation study.

INTRODUCTION: Utility instruments are used to assess patients' health-related quality of life for cost-utility analysis (CUA). However, for cancer patients, the dimensions of generic utility instruments may not capture all the information relevant to the impact of cancer. Cancer-specific utilities provide a useful alternative. Under the auspices of the Multi-Attribute Utility in Cancer Consortium, a cancer-specific utility algorithm was derived from the FACT-G. The new FACT-8D contains eight dimensions: pain, fatigue, nausea, sleep, work, support from family/friends, sadness, and worry health will get worse. The aim of the study was to obtain a Canadian value set for the FACT-8D. METHODS: A discrete choice experiment was administered to a Canadian general population online panel, quota sampled by age, sex, and province/territory of residence. Respondents provided responses to 16 choice sets. Each choice set consisted of two health states described by the FACT-8D dimensions plus an attribute representing survival duration. Sample weights were applied and the responses were analyzed using conditional logistic regression, parameterized to fit the quality-adjusted life year framework. The results were converted into utility weights by evaluating the marginal rate of substitution between each level of each FACT-8D dimension with respect to duration. RESULTS: 2228 individuals were recruited. The analysis dataset included n = 1582 individuals, who completed at least one choice set; of which, n = 1501 completed all choice sets. After constraining to ensure monotonicity in the utility function, the largest decrements were for the highest levels of pain (- 0.38), nausea (- 0.30), and problems doing work (- 0.23). The decrements of the remaining dimensions ranged from - 0.08 to - 0.18 for their highest levels. The utility of the worst possible health state was defined as - 0.65, considerably worse than dead. CONCLUSIONS: The largest impacts on utility included three generic dimensions (i.e., pain, support, and work) and nausea, a symptom caused by cancer (e.g., brain tumours, gastrointestinal tumours, malignant bowel obstruction) and by common treatments (e.g., chemotherapy, radiotherapy, opioid analgesics). This may make the FACT-8D more informative for CUA evaluating in many cancer contexts, an assertion that must now be tested empirically in head-to-head comparisons with generic utility measures.

A Comparison of Generic and Condition-Specific Preference-Based Measures Using Data From Nivolumab Trials: EQ-5D-3L, Mapping to the EQ-5D-5L, and European Organisation for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions.

OBJECTIVES: There is growing interest in condition-specific preference measures, including the European Organisation for Research and Treatment of Cancer Quality of Life Utility Measure-Core 10 Dimensions (QLU-C10D). This research assessed the implications of using utility indices on the basis of the EQ-5D-3L, a mapping of EQ-5D-3L to the EQ-5D-5L, and the QLU-C10D, and compared their psychometric properties. METHODS: Data were taken from 8 phase 3 randomized controlled trials of nivolumab with or without ipilimumab for the treatment of solid tumors. Utilities for progression-related states were calculated using the UK and English value sets and incremental quality-adjusted life-years (QALYs) derived from established UK cost-effectiveness models. The psychometric properties of the utility indices were assessed using pooled trial data. RESULTS: Compared with the EQ-5D-3L index, the mapped EQ-5D-5L index yielded an average of 6% more and the QLU-C10D index an average of 2% fewer incremental QALYs for nivolumab versus comparators. All indices could differentiate between groups defined by performance status, cancer stage, or self-reported health status at baseline and detect meaningful changes in performance status, tumor response, health status, and quality of life over approximately 12 weeks of treatment. CONCLUSIONS: The lower QALY yield of the QLU-C10D was balanced by evidence of greater validity and responsiveness. Benefits gained from using the QLU-C10D may be apparent when treatments affect targeted symptoms and functional aspects, including sleep, bowel function, appetite, nausea, and fatigue. The observed differences in QALYs may not be sufficiently large to affect health technology assessment decisions.

The Functional Assessment of Cancer Therapy Eight Dimension (FACT-8D), a Multi-Attribute Utility Instrument Derived From the Cancer-Specific FACT-General (FACT-G) Quality of Life Questionnaire: Development and Australian Value Set.

OBJECTIVES: To develop a cancer-specific multi-attribute utility instrument derived from the Functional Assessment of Cancer Therapy - General (FACT-G) health-related quality of life (HRQL) questionnaire. METHODS: We derived a descriptive system based on a subset of the 27-item FACT-G. Item selection was informed by psychometric analyses of existing FACT-G data (n = 6912) and by patient input (n = 82). We then conducted an online valuation survey, with participants recruited via an Australian general population online panel. A discrete choice experiment (DCE) was used, with attributes being the HRQL dimensions of the descriptive system and survival duration, and 16 choice-pairs per participant. Utility decrements were estimated with conditional logit and mixed logit modeling. RESULTS: Eight HRQL dimensions were included in the descriptive system: pain, fatigue, nausea, sleep, work, social support, sadness, and future health worry; each with 5 levels. Of 1737 panel members who accessed the valuation survey, 1644 (95%) completed 1 or more DCE choice-pairs and were included in analyses. Utility decrements were generally monotonic; within each dimension, poorer HRQL levels generally had larger utility decrements. The largest utility decrements were for the highest levels of pain (-0.40) and nausea (-0.28). The worst health state had a utility of -0.54, considerably worse than dead. CONCLUSIONS: A descriptive system and preference-based scoring approach were developed for the FACT-8D, a new cancer-specific multi-attribute utility instrument derived from the FACT-G. The Australian value set is the first of a series of country-specific value sets planned that can facilitate cost-utility analyses based on items from the FACT-G and related FACIT questionnaires containing FACT-G items.

U.K. utility weights for the EORTC QLU-C10D.

The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality of life questionnaire, EORTC QLQ-C30. It contains 10 dimensions (physical functioning, role functioning, social functioning, emotional functioning, pain, fatigue, sleep, appetite, nausea, bowel problems), each with four levels. The aim of this study was to provide U.K. general population utility weights for the QLU-C10D. A U.K. online panel was quota-sampled to align the sample to the general population proportions of sex and age (≥18 years). The online valuation survey included a discrete choice experiment (DCE). Each participant was asked to complete 16 choice-pairs, each comprising two QLU-C10D health states plus duration. DCE data were analysed using conditional logistic regression to generate utility weights. Data from 2,187 respondents who completed at least one choice set were included in the DCE analysis. The final U.K. QLU-C10D utility weights comprised decrements for each level of each health dimension. For nine of the 10 dimensions (all except appetite), the expected monotonic pattern was observed across levels: Utility decreased as severity increased. For the final model, consistent monotonicity was achieved by merging inconsistent adjacent levels for appetite. The largest utility decrements were associated with physical functioning and pain. The worst possible health state (the worst level of each dimension) is -0.083, which is considered slightly worse than being dead. The U.K.-specific utility weights will enable cost-utility analysis (CUA) for the economic evaluation of new oncology therapies and technologies in the United Kingdom, where CUA is commonly used to inform resource allocation.

The EORTC CAT Core-The computer adaptive version of the EORTC QLQ-C30 questionnaire.

BACKGROUND: To optimise measurement precision, relevance to patients and flexibility, patient-reported outcome measures (PROMs) should ideally be adapted to the individual patient/study while retaining direct comparability of scores across patients/studies. This is achievable using item banks and computerised adaptive tests (CATs). The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 (QLQ-C30) is one of the most widely used PROMs in cancer research and clinical practice. Here we provide an overview of the research program to develop CAT versions of the QLQ-C30's 14 functional and symptom domains. METHODS: The EORTC Quality of Life Group's strategy for developing CAT item banks consists of: literature search to identify potential candidate items; formulation of new items compatible with the QLQ-C30 item style; expert evaluations and patient interviews; field-testing and psychometric analyses, including factor analysis, item response theory calibration and simulation of measurement properties. In addition, software for setting up, running and scoring CAT has been developed. RESULTS: Across eight rounds of data collections, 9782 patients were recruited from 12 countries for the field-testing. The four phases of development resulted in a total of 260 unique items across the 14 domains. Each item bank consists of 7-34 items. Psychometric evaluations indicated higher measurement precision and increased statistical power of the CAT measures compared to the QLQ-C30 scales. Using CAT, sample size requirements may be reduced by approximately 20-35% on average without loss of power. CONCLUSIONS: The EORTC CAT Core represents a more precise, powerful and flexible measurement system than the QLQ-C30. It is currently being validated in a large independent, international sample of cancer patients.

Assessment of content validity for patient-reported outcome measures used in patients with non-muscle invasive bladder cancer: a systematic review.

OBJECTIVE: Non-muscle invasive bladder cancer (NMIBC) is a chronic condition requiring ongoing treatment and endoscopic examinations that are frequent and can be life-long. To ensure the comprehensive assessment of the benefits and harms of treatments for NMIBC, the impact on important and relevant patient-reported outcomes (PROs) should be determined. We systematically reviewed the NMIBC PRO literature to determine the suitability of available PRO measures (PROMs) for use in evaluating patient outcomes in NMIBC research. METHODS: We searched six electronic databases, reference lists, and key authors. Two reviewers independently applied inclusion and quality criteria and extracted findings. PROM domains, item content, and content coverage and relevance were determined for identified PROMs. Content validity was assessed against an empirically derived NMIBC-specific conceptual framework that includes 11 PRO domains and 19 sub-domains. RESULTS: Seventeen studies assessed PROs related to NMIBC and treatment impact. From these studies, 11 PROMs were identified, including three generic, three cancer-specific, and five symptom-specific. None of the PROMs cover all PRO domains important in NMIBC as assessed against our conceptual framework. The EORTC QLQ-C30 plus the NMIBC24 module was best aligned to the conceptual model, but failed to represent six outcomes important to NMIBC patients. CONCLUSIONS: Currently, some outcomes important in NMIBC are inadequately covered by generic and cancer-specific measures despite similar conceptual models. This review identified gaps in the literature regarding assessment of symptoms and other PROs considered important by NMIBC patients. Careful consideration of PROM item content is required when selecting outcome measures for use in future NMIBC clinical trials to ensure that appropriate measures are used to assess outcomes that matter to patients.

Australian Utility Weights for the EORTC QLU-C10D, a Multi-Attribute Utility Instrument Derived from the Cancer-Specific Quality of Life Questionnaire, EORTC QLQ-C30.

BACKGROUND: The EORTC QLU-C10D is a new multi-attribute utility instrument derived from the widely used cancer-specific quality-of-life (QOL) questionnaire, EORTC QLQ-C30. The QLU-C10D contains ten dimensions (Physical, Role, Social and Emotional Functioning; Pain, Fatigue, Sleep, Appetite, Nausea, Bowel Problems), each with four levels. To be used in cost-utility analysis, country-specific valuation sets are required. OBJECTIVE: The aim of this study was to provide Australian utility weights for the QLU-C10D. METHODS: An Australian online panel was quota-sampled to ensure population representativeness by sex and age (≥ 18 years). Participants completed a discrete choice experiment (DCE) consisting of 16 choice-pairs. Each pair comprised two QLU-C10D health states plus life expectancy. Data were analysed using conditional logistic regression, parameterised to fit the quality-adjusted life-year framework. Utility weights were calculated as the ratio of each QOL dimension-level coefficient to the coefficient on life expectancy. RESULTS: A total of 1979 panel members opted in, 1904 (96%) completed at least one choice-pair, and 1846 (93%) completed all 16 choice-pairs. Dimension weights were generally monotonic: poorer levels within each dimension were generally associated with greater utility decrements. The dimensions that impacted most on choice were, in order, Physical Functioning, Pain, Role Functioning and Emotional Functioning. Oncology-relevant dimensions with moderate impact were Nausea and Bowel Problems. Fatigue, Trouble Sleeping and Appetite had relatively small impact. The value of the worst health state was -0.096, somewhat worse than death. CONCLUSIONS: This study provides the first country-specific value set for the QLU-C10D, which can facilitate cost-utility analyses when applied to data collected with the EORTC QLQ-C30, prospectively and retrospectively.

A conceptual framework for patient-reported outcomes in non-muscle invasive bladder cancer.

PURPOSE: Non-muscle invasive bladder cancer (NMIBC) is a chronic condition requiring repeated treatment and endoscopic examinations that can be life-long. In this context, health-related quality of life (HRQOL) is important to patients and managing clinicians, and integral to treatment recommendations for NMIBC. The aim of this study was to develop a conceptual framework of patient-reported NMIBC symptoms, treatment side effects, and HRQOL impacts from three sources: (1) literature, (2) patients and (3) treating clinicians. METHODS: First, we undertook a scoping literature review for studies reporting patient-reported outcomes associated with NMIBC. Outcomes were extracted and grouped conceptually. Then, we conducted semi-structured interviews with patients with NMIBC and treating clinicians. Patients were asked about symptoms and HRQOL impacts experienced from their NMIBC and treatments. Clinicians were asked about commonly reported outcomes, and outcomes they felt were important to assess clinically. Interviews were audio recorded, transcribed and content analysed. RESULTS: A total of 125 symptom- and functioning-related expressions from 18 studies, 26 patients and 20 clinicians were coded into three themes and 18 sub-themes. Patients commonly reported blood in urine and frequent urination. Clinicians considered BCG sepsis and flu-like symptoms important outcomes to assess during treatment for NMIBC. CONCLUSION: Our empirically derived conceptual framework identifies patient-reported outcomes that are important to people with NMIBC, provides the basis for the development of a new NMIBC-specific symptom index, and guides the design of a comprehensive PRO assessment plan for clinical practice in NMIBC and future clinical trials of treatments for NMIBC.

The Added Value of Analyzing Pooled Health-Related Quality of Life Data: A Review of the EORTC PROBE Initiative.

BACKGROUND: The European Organisation for Research and Treatment of Cancer (EORTC) Patient-Reported Outcomes and Behavioural Evidence (PROBE) initiative was established to investigate critical topics to better understand health-related quality of life (HRQOL) of cancer patients and to educate clinicians, policy makers, and healthcare providers. METHODS: The aim of this paper is to review the major research outcomes of the pooled analysis of HRQOL data along with the clinical data. We identified 30 pooled EORTC randomized controlled trials (RCTs), 18 NCIC-Clinical Trials Group RCTs, and two German Ovarian Cancer Study Group RCTs, all using the EORTC QLQ-C30. All statistical tests were two-sided. RESULTS: Evidence was found that HRQOL data can offer prognostic information beyond clinical measures and improve prognostic accuracy in cancer RCTs (by 5.9%-8.3%). Moreover, models that considered both patient- and clinician-reported scores gained more prognostic overall survival accuracy for fatigue (P < .001), vomiting (P = .01), nausea (P < .001), and constipation (P = .01). Greater understanding of the association between symptom and/or functioning scales was developed by identifying physical, psychological, and gastrointestinal clusters. Additionally, minimally important differences in interpreting HRQOL changes for improvement and deterioration were found to vary across different patient populations and disease stages. Finally, HRQOL scores are statistically significantly affected by deviations from the intended time point at which the questionnaire is completed. CONCLUSIONS: The use of existing pooled data shows that it is possible to learn about general aspects of cancer HRQOL and methodology. Our work shows that setting up international pooled datasets holds great promise for understanding patients' unmet psychosocial needs and calls for additional empirical investigation to improve clinical care and understand cancer through retrospective HRQOL analyses.

The physical functioning and mental health of informal carers: evidence of care-giving impacts from an Australian population-based cohort.

Informal carers represent a substantial proportion of the population in many countries and health is an important factor in their capacity to continue care-giving. This study investigated the impact of care-giving on the mental and physical health of informal carers, taking account of contextual factors, including family and work. We examined health changes from before care-giving commenced to 2 and 4 years after, using longitudinal data from the Household Income and Labour Dynamics in Australia survey. The sample comprised 424 carers and 424 propensity score-matched non-carers. Health was self-assessed, measured with the SF-36 Health Survey Mental Health (MH) and Physical Functioning (PF) scales. Care-giving was classified as non-carer, low (<5 hours/week), moderate (5-19 hours/week) and high (20 or more hours/week). PF and MH change scores were regressed on baseline scores, care-giving, covariates (including work, family and socio-demographic characteristics) and interactions to identify impacts for subgroups. The physical and mental health impacts differed by gender, and care-giving hours and carer work hours were important contextual factors. Deterioration in both PF and MH was worse for females after 2 years and deterioration in MH was worse for males after 4 years. Among carers aged 40-64 years, there was a 17-point decline in PF (P = 0.009) and a 14-point decline in MH (P < 0.0001) after 2 years for female high caregivers working full-time and 9.3 point improvement (P = 0.02) for non-working male high caregivers. Change was not significant for non-carers. The study found that not all carers suffer adverse health impacts; however, the combination of high levels of care-giving with workforce participation can increase the risk of negative physical and mental health effects (particularly in female carers). Working carers providing high levels of care represent a vulnerable subgroup where supportive and preventive services might be focused.

The Quality of Life Questionnaire Core 30 (QLQ-C30) and Functional Assessment of Cancer-General (FACT-G) differ in responsiveness, relative efficiency, and therefore required sample size.

OBJECTIVES: Quality of Life Questionnaire Core 30 (QLQ-C30) and Functional Assessment of Cancer Therapy-General (FACT-G) are widely used cancer-specific health-related quality of life (HRQOL) questionnaires. We aimed to compare their responsiveness with clinically important effects and statistical efficiency to detect such effects. STUDY DESIGN AND SETTING: Secondary analysis of QLQ-C30 and FACT-G data from a randomized controlled trial of Medical Qigong (n = 162 heterogeneous cancer patients). Difference in responsiveness (DR) and relative efficiency (RE) were calculated for five domains. RESULTS: FACT-G total score was more efficient than QLQ-C30 global scale for detecting change within the intervention arm [RE = 0.31 (0.083, 0.69)] and comparing change between trial arms [RE = 0.17 (0.009, 0.58)]. In the social domain, the QLQ-C30 scale was more responsive [DR = 0.28 (0.024, 0.54)] and more efficient within arm only [RE = 5.25 (1.21, 232.26)]. In the physical, functional/role, and emotional domains, neither questionnaire was more responsive or efficient. CONCLUSION: FACT-G would require about one-third the sample of QLQ-C30 to detect a given change in overall HRQOL, whereas in the social domain, it would require five times the sample size. FACT-G won advantage in overall HRQOL by reduced "noise" (smaller standard deviation achieved by summing across 27 items), whereas QLQ-C30 won advantage in the social domain via a larger "signal" (achieved through well-targeted item content).

An Australian discrete choice experiment to value eq-5d health states.

Conventionally, generic quality-of-life health states, defined within multi-attribute utility instruments, have been valued using a Standard Gamble or a Time Trade-Off. Both are grounded in expected utility theory but impose strong assumptions about the form of the utility function. Preference elicitation tasks for both are complicated, limiting the number of health states that each respondent can value and, therefore, that can be valued overall. The usual approach has been to value a set of the possible health states and impute values for the remainder. Discrete Choice Experiments (DCEs) offer an attractive alternative, allowing investigation of more flexible specifications of the utility function and greater coverage of the response surface. We designed a DCE to obtain values for EQ-5D health states and implemented it in an Australia-representative online panel (n = 1,031). A range of specifications investigating non-linear preferences with respect to time and interactions between EQ-5D levels were estimated using a random-effects probit model. The results provide empirical support for a flexible utility function, including at least some two-factor interactions. We then constructed a preference index such that full health and death were valued at 1 and 0, respectively, to provide a DCE-based algorithm for Australian cost-utility analyses.

Conceptual, classification or causal: models of health status and health-related quality of life.

Instruments intended to assess health-related quality of life (HRQOL) and health status are widely used in research and clinical practice, but with little conceptual guidance there is some uncertainty about what it is that these instruments are actually tapping. Causal models have the potential to provide the required conceptual guidance, not only placing commonly discussed health concepts on a firm scientific foundation, but also allowing medical and psychosocial interventions to be developed in a more focused and efficient manner. Several models, some postulating causal relations, have been proposed over many years, and some have been supported by data. The development and validation of these models has, however, been conducted in a piecemeal fashion. The imperative to develop tailored, cost-effective interventions requires a synthesized approach to developing and testing causal models.

Psychological morbidity and quality of life of ethnic minority patients with cancer: a systematic review and meta-analysis.

BACKGROUND: Ethnic minority is associated with higher cancer incidence and poorer survival than is being in the majority group. We did a systematic review and meta-analysis to assess whether psychological morbidity and health-related quality of life (HRQoL) were affected by minority status. METHODS: We searched Medline, AMED, PsycINFO, Embase, CENTRAL, CINAHL, PubMed, Sociological Abstracts, and Web of Science for English-language articles published between Jan 1, 1995, and October, 2009. Articles were eligible if they reported original data on anxiety, depression, distress (for psychological morbidity), or HRQoL in minority and majority cancer patients or survivors. Minority status was defined as being an immigrant or having an ethnic, linguistic, or religious background different to the majority of the population in the country where the research was done. We excluded African Americans and indigenous groups. Eligible articles were rated for quality of reporting, external validity, internal validity, sample size, and power. Each quality criterion was rated independently by two reviewers until inter-rater reliability was achieved. In a meta-analysis we compared mean scores adjusted for socioeconomic status and other sociodemographic and clinical variables, where available. Effect sizes greater than 0·5 and 95% CI that included 0·5 or -0·5 were deemed clinically important, with negative values indicating worse outcomes in minority patients. We assessed publication bias by estimating the number of potential unpublished studies and the number of non-signficant studies with p=0·05 required to produce a non-significant overall result. FINDINGS: We identified 21 eligible articles that included 18 datasets collected in the USA and one in each of Canada, Romania, and the UK. Ethnic minority groups were Hispanic, Asian or Pacific Islander, or Hungarian (one dataset). Overall, we found minority versus majority groups to have significantly worse distress (mean difference -0·37, 95% CI -0·46 to -0·28; p<0·0001), depression (-0·23, -0·36 to -0·11; p=0·0003), and overall HRQoL (-0·33, -0·58 to -0·07; p=0·013). Further analyses found disparities to be specific to Hispanic patients in the USA, in whom poorer outcomes were consistent with potentially clinically important differences for distress (effect size -0·37, 95% CI -0·54 to -0·20; p<0·0001), social HRQoL (-0·45, -0·87 to -0·03; p=0·035), and overall HRQoL (-0·49, -0·78 to -0.20; p=0·0008). Results were significantly heterogeneous for overall HRQoL and all domains. Tests for interaction, for adjusted versus unadjusted and comparisons of high-quality, medium-quality, and low-quality articles, were generally non-significant, which suggests no bias. We found no evidence of any substantive publication bias. INTERPRETATION: Hispanic cancer patients in the USA, but not other ethnic minority groups, report significantly worse distress, depression, social HRQoL, and overall HRQoL than do majority patients, of which all but depression might be clinically important. Heterogeneous results might, however, have limited the interpretation. Data for other minority groups and for anxiety are scarce. More studies are needed from outside the USA. Future reports should more clearly describe their minority group samples and analyses should control for clinical and sociodemographic variables known to predict outcomes. Understanding of why outcomes are poor in US Hispanic patients is needed to inform the targeting of interventions. FUNDING: Prince of Wales Hospital, Sydney, Australia.