Improving decision-making: Deriving patient-valued utilities from a disease-specific quality of life questionnaire for evaluating clinical trials

The aim of the work reported in this thesis was to develop a scoring algorithm that converts ratings from a validated disease-specific quality of life questionnaire called the Utility-Based Questionnaire-Cancer (UBQ-C) into a utility index that is designed for evaluating clinical trials to inform clinical decisions about cancer treatments. The UBQ-C includes a scale for global health status (1 item); and subscales for physical function (3 items), social/usual activities (4 items), self-care (1 item), and distresses due to physical and psychological symptoms (21 items). Data from three studies was used. A valuation survey consisted of patients with advanced cancer (n=204) who completed the UBQ-C and assigned time-trade-off utilities about their own health state. Clinical trials were of chemotherapy for advanced (n=325) and early (n=126) breast cancer. A scoring algorithm was derived to convert the subscales into a subset index, and combine it with the global scale into an overall quality of life index, which was converted to a utility index with a power transformation. Optimal weights were assigned to the subscales that reflected their correlations with a global scale in each study. The derived utilities were validated by comparison with other patient characteristics. Each trial was evaluated in terms of differences in utility between treatment groups. In the valuation survey, the weights (range 0 to 1) for the subset index were: physical function 0.28, social/usual activities 0.06, self-care 0.01, and distresses 0.64. Weights for the overall quality of life index were health status 0.65 and subset index 0.35. The mean of the utility index scores was similar to the mean of the time trade-off utilities (0.92 vs. 0.91, p=0.6). The weights were adjusted in each clinical trial. The utility index was substantially correlated with other measures of quality of life, discriminated between breast cancer that was advanced rather than early (means 0.88 vs 0.94, p<0.0001), and was responsive to toxic effects of chemotherapy in early breast cancer (mean change 0.07, p<0.0001). There were trends to better mean scores on the utility index for patients allocated to standard-dose versus high-dose chemotherapy in the early cancer trial (p=0.1), and oral versus intravenous chemotherapy in the advanced cancer trial (p=0.2). In conclusion, data from a simple, self-rated, disease-specific questionnaire can be converted into a utility index based on cancer patients’ preferences. The index can be optimised in different clinical contexts to reflect the relative importance of different aspects of quality of life to the patients in a trial. The index can be used to generate utility scores and quality-adjusted life-years in clinical trials. It enables the evaluation of the net effect of treatments on health-related quality of life (accounting for trade-offs between disparate aspects); the evaluation of the net benefit of treatments (accounting for trade-offs between quality of life and survival); and an alternate perspective for comparing the incremental cost-effectiveness of treatments (accounting for trade-offs between net benefit and costs). The practical significance of this work is to facilitate the integration of data about health-related quality of life with traditional trial endpoints such as survival and tumour response. This will better inform clinical decision-making, and provide an alternate viewpoint for economic decision-making. Broadly, it will help patients, clinicians and health funders make better decisions about cancer treatments, by considering potential trade-offs between effects on survival and health-related quality of life

Improving decision-making: Deriving patient-valued utilities from a disease-specific quality of life questionnaire for evaluating clinical trials

The aim of the work reported in this thesis was to develop a scoring algorithm that converts ratings from a validated disease-specific quality of life questionnaire called the Utility-Based Questionnaire-Cancer (UBQ-C) into a utility index that is designed for evaluating clinical trials to inform clinical decisions about cancer treatments. The UBQ-C includes a scale for global health status (1 item); and subscales for physical function (3 items), social/usual activities (4 items), self-care (1 item), and distresses due to physical and psychological symptoms (21 items). Data from three studies was used. A valuation survey consisted of patients with advanced cancer (n=204) who completed the UBQ-C and assigned time-trade-off utilities about their own health state. Clinical trials were of chemotherapy for advanced (n=325) and early (n=126) breast cancer. A scoring algorithm was derived to convert the subscales into a subset index, and combine it with the global scale into an overall quality of life index, which was converted to a utility index with a power transformation. Optimal weights were assigned to the subscales that reflected their correlations with a global scale in each study. The derived utilities were validated by comparison with other patient characteristics. Each trial was evaluated in terms of differences in utility between treatment groups. In the valuation survey, the weights (range 0 to 1) for the subset index were: physical function 0.28, social/usual activities 0.06, self-care 0.01, and distresses 0.64. Weights for the overall quality of life index were health status 0.65 and subset index 0.35. The mean of the utility index scores was similar to the mean of the time trade-off utilities (0.92 vs. 0.91, p=0.6). The weights were adjusted in each clinical trial. The utility index was substantially correlated with other measures of quality of life, discriminated between breast cancer that was advanced rather than early (means 0.88 vs 0.94, p<0.0001), and was responsive to toxic effects of chemotherapy in early breast cancer (mean change 0.07, p<0.0001). There were trends to better mean scores on the utility index for patients allocated to standard-dose versus high-dose chemotherapy in the early cancer trial (p=0.1), and oral versus intravenous chemotherapy in the advanced cancer trial (p=0.2). In conclusion, data from a simple, self-rated, disease-specific questionnaire can be converted into a utility index based on cancer patients’ preferences. The index can be optimised in different clinical contexts to reflect the relative importance of different aspects of quality of life to the patients in a trial. The index can be used to generate utility scores and quality-adjusted life-years in clinical trials. It enables the evaluation of the net effect of treatments on health-related quality of life (accounting for trade-offs between disparate aspects); the evaluation of the net benefit of treatments (accounting for trade-offs between quality of life and survival); and an alternate perspective for comparing the incremental cost-effectiveness of treatments (accounting for trade-offs between net benefit and costs). The practical significance of this work is to facilitate the integration of data about health-related quality of life with traditional trial endpoints such as survival and tumour response. This will better inform clinical decision-making, and provide an alternate viewpoint for economic decision-making. Broadly, it will help patients, clinicians and health funders make better decisions about cancer treatments, by considering potential trade-offs between effects on survival and health-related quality of life

Deriving a preference-based measure for cancer using the EORTC QLQ-C30 : a confirmatory versus exploratory approach

Background: To derive preference-based measures from various condition-specific descriptive health-related quality of life (HRQOL) measures. A general 2-stage method is evolved: 1) an item from each domain of the HRQOL measure is selected to form a health state classification system (HSCS); 2) a sample of health states is valued and an algorithm derived for estimating the utility of all possible health states. The aim of this analysis was to determine whether confirmatory or exploratory factor analysis (CFA, EFA) should be used to derive a cancer-specific utility measure from the EORTC QLQ-C30. Methods: Data were collected with the QLQ-C30v3 from 356 patients receiving palliative radiotherapy for recurrent or metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter based on a conceptual model (the established domain structure of the QLQ-C30: physical, role, emotional, social and cognitive functioning, plus several symptoms) and clinical considerations (views of both patients and clinicians about issues relevant to HRQOL in cancer). The dimensions determined by each method were then subjected to item response theory, including Rasch analysis. Results: CFA results generally supported the proposed conceptual model, with residual correlations requiring only minor adjustments (namely, introduction of two cross-loadings) to improve model fit (increment χ2(2) = 77.78, p 75% observation at lowest score), 6 exhibited misfit to the Rasch model (fit residual > 2.5), none exhibited disordered item response thresholds, 4 exhibited DIF by gender or cancer site. Upon inspection of the remaining items, three were considered relatively less clinically important than the remaining nine. Conclusions: CFA appears more appropriate than EFA, given the well-established structure of the QLQ-C30 and its clinical relevance. Further, the confirmatory approach produced more interpretable results than the exploratory approach. Other aspects of the general method remain largely the same. The revised method will be applied to a large number of data sets as part of the international and interdisciplinary project to develop a multi-attribute utility instrument for cancer (MAUCa)

Developing a clinical pathway for the identification and management of anxiety and depression in adult cancer patients: an online Delphi consensus process

Purpose: People with cancer and their families experience high levels of psychological morbidity. However many cancer services do not routinely screen patients for anxiety and depression and there are no standardized clinical referral pathways. This study aimed to establish consensus on elements of a draft clinical pathway tailored to the Australian context. Methods: A two-round Delphi study was conducted to gain consensus among Australian oncology and psycho-oncology clinicians about the validity of 39 items that form the basis of a clinical pathway that includes screening, assessment, referral and stepped-care management of anxiety and depression in the context of cancer. The expert panel comprised 87 multidisciplinary clinician members of the Australian Psycho-oncology Cooperative Research Group (PoCoG). Respondents rated their level of agreement with each statement on a 5-point likert scale. Consensus was defined as >80% of respondents scoring within 2 points on the likert scale. Results: Consensus was reached for 21 of 39 items, and a further 15 items approached consensus except for specific contextual factors, after 2 Delphi rounds. Formal screening for anxiety and depression, a stepped care model of management and recommendations for inclusion of length of treatment and time to review were endorsed. Consensus was not reached on items related to roles and responsibilities, particularly those not applicable across cancer settings. Conclusions: This study identified a core set of evidence- and consensus-based principles considered essential to a stepped care model of care incorporating identification, referral and management of anxiety and depression in adult cancer patients.This study was funded by Sydney Catalyst Translational Cancer Research Centr

Clinical pathway for the screening, assessment and management of anxiety and depression in adult cancer patients: Australian guidelines.

Purpose A clinical pathway for anxiety and depression in adult cancer patients was developed to guide best practice in Australia. Methods The pathway was based on a rapid review of existing guidelines, systematic reviews and meta-analyses, stakeholder interviews, a Delphi process with 87 multi-disciplinary stakeholders and input from a multidisciplinary advisory panel. Results The pathway recommends formalised routine screening for anxiety and depression in patients with cancer at key points in the patient’s journey. The Edmonton Symptom Assessment System (ESAS) or Distress Thermometer (DT) with problem checklist are recommended as brief screening tools, combined with a more detailed tool, such as the Hospital Anxiety and Depression Scale (HADS), to identify possible cases. A structured clinical interview will be required to confirm diagnosis. When anxiety or depression is identified it is recommended one person in a treating team takes responsibility for co-ordinating appropriate assessment, referral and follow-up (not necessarily carrying these out themselves). A stepped care model of intervention is proposed, beginning with the least intensive available that is still likely to provide significant health gain. The exact intervention, treatment length and follow up timelines as well as professionals involved, are provided as a guide only. Each service should identify their own referral network based on local resources and current service structure, as well as patient preference. Discussion This clinical pathway will assist cancer services to design their own systems to detect and manage anxiety and depression in their patients, to improve the quality of care

Oral cannabinoid-rich THC/CBD cannabis extract for secondary prevention of chemotherapy-induced nausea and vomiting : a study protocol for a pilot and definitive randomised double-blind placebo-controlled trial (CannabisCINV)

INTRODUCTION: Chemotherapy-induced nausea and vomiting (CINV) remains an important issue for patients receiving chemotherapy despite guideline-consistent antiemetic therapy. Trials using delta-9-tetrahydrocannabinol-rich (THC) products demonstrate limited antiemetic effect, significant adverse events and flawed study design. Trials using cannabidiol-rich (CBD) products demonstrate improved efficacy and psychological adverse event profile. No definitive trials have been conducted to support the use of cannabinoids for this indication, nor has the potential economic impact of incorporating such regimens into the Australian healthcare system been established. CannabisCINV aims to assess the efficacy, safety and cost-effectiveness of adding TN-TC11M, an oral THC/CBD extract to guideline-consistent antiemetics in the secondary prevention of CINV. METHODS AND ANALYSIS: The current multicentre, 1:1 randomised cross-over, placebo-controlled pilot study will recruit 80 adult patients with any malignancy, experiencing CINV during moderate to highly emetogenic chemotherapy despite guideline-consistent antiemetics. Patients receive oral TN-TC11M (THC 2.5mg/CBD 2.5 mg) capsules or placebo capsules three times a day on day -1 to day 5 of cycle A of chemotherapy, followed by the alternative drug regimen during cycle B of chemotherapy and the preferred drug regimen during cycle C. The primary endpoint is the proportion of subjects attaining a complete response to CINV. Secondary and tertiary endpoints include regimen tolerability, impact on quality of life and health system resource use. The primary assessment tool is patient diaries, which are filled from day -1 to day 5. A subsequent randomised placebo-controlled parallel phase III trial will recruit a further 250 patients. ETHICS AND DISSEMINATION: The protocol was approved by ethics review committees for all participating sites. Results will be disseminated in peer-reviewed journals and at scientific conferences.Tilray. PROTOCOL VERSION: 2.0, 9 June 2017

ROR1 and ROR2 expression in pancreatic cancer

Background: The Wnt receptors ROR1 and ROR2 are generating increased interest as cancer therapeutic targets but remain understudied in pancreatic ductal adenocarcinoma (PDAC). Compared to canonical Wnt/ β-catenin signalling, the role of noncanonical Wnt signalling in PDAC remains largely unknown. Only one study has investigated the prognostic significance of the noncanonical Wnt signalling receptor, ROR2 in PDAC. No studies have investigated the prognostic role of ROR1 in PDAC. Methods: Here, we performed analysis of ROR1 and ROR2 mRNA expression in three publicly available datasets ICGC-PACA-AU (n = 81), TCGA-PAAD (n = 150) and CPTAC-PDAC (n = 137). ROR1 and ROR2 protein expression from the CPTAC-PDAC discovery cohort were also analysed. Immunohistochemistry (IHC) using the validated anti ROR1 monoclonal antibody (4A5) was performed on the Australian Pancreatic Cancer Genome Initiative (APGI) cohort of PDAC samples (n = 152). Association between ROR1 cytoplasmic staining intensity and clinicopathological parameters including stage, grade and overall survival (OS) was investigated. Results: High ROR1 mRNA expression levels correlated with a favourable OS outcome in all of the ICGC-PACA-AU, TCGA-PAAD and CPTAC-PDAC cohorts. ROR1 protein expression was not associated with stage, grade or OS in the APGI cohort. Conclusion: ROR1 and ROR2 have potential as prognostic markers when measured at the mRNA level in PDAC. Our IHC cohort did not support ROR1 protein expression in predicting OS, and highlighted the discrepancy of prognostic biomarkers when measured by MS, IHC and RNAseq

Accurate isolation and detection of circulating tumor cells using enrichment-free multiparametric high resolution imaging

IntroductionThe reliable and accurate detection of rare circulating tumor cells (CTCs) from cancer patient blood samples promises advantages in both research and clinical applications. Numerous CTC detection methods have been explored that rely on either the physical properties of CTCs such as density, size, charge, and/or their antigen expression profiles. Multiple factors can influence CTC recovery including blood processing method and time to processing. This study aimed to examine the accuracy and sensitivity of an enrichment-free method of isolating leukocytes (AccuCyte® system) followed by immunofluorescence staining and high-resolution imaging (CyteFinder® instrument) to detect CTCs.MethodHealthy human blood samples, spiked with cancer cells from cancer cell lines, as well as blood samples obtained from 4 subjects diagnosed with cancer (2 pancreatic, 1 thyroid, and 1 small cell lung) were processed using the AccuCyte-CyteFinder system to assess recovery rate, accuracy, and reliability over a range of processing times.ResultsThe AccuCyte-CyteFinder system was highly accurate (95.0%) at identifying cancer cells in spiked-in samples (in 7.5 mL of blood), even at low spiked-in numbers of 5 cells with high sensitivity (90%). The AccuCyte-CyteFinder recovery rate (90.9%) was significantly higher compared to recovery rates obtained by density gradient centrifugation (20.0%) and red blood cell lysis (52.0%). Reliable and comparable recovery was observed in spiked-in samples and in clinical blood samples processed up to 72 hours post-collection. Reviewer analysis of images from spiked-in and clinical samples resulted in high concordance (R-squared value of 0.998 and 0.984 respectively).DiscussionThe AccuCyte-CyteFinder system is as an accurate, sensitive, and clinically practical method to detect and enumerate cancer cells. This system addresses some of the practical logistical challenges in incorporating CTCs as part of routine clinical care. This could facilitate the clinical use of CTCs in guiding precision, personalized medicine

Predicting Outcomes in Men With Metastatic Nonseminomatous Germ Cell Tumors (NSGCT): Results From the IGCCCG Update Consortium

Purpose: The classification of the International Germ Cell Cancer Collaborative Group (IGCCCG) plays a pivotal role in the management of metastatic germ cell tumors but relies on data of patients treated between 1975 and 1990. Materials and methods: Data on 9,728 men with metastatic nonseminomatous germ cell tumors treated with cisplatin- and etoposide-based first-line chemotherapy between 1990 and 2013 were collected from 30 institutions or collaborative groups in Europe, North America, and Australia. Clinical trial and registry data were included. Primary end points were progression-free survival (PFS) and overall survival (OS). The survival estimates were updated for the current era. Additionally, a novel prognostic model for PFS was developed in 3,543 patients with complete information on potentially relevant variables. The results were validated in an independent data set. Results: Compared with the original IGCCCG publication, 5-year PFS remained similar in patients with good prognosis with 89% (87%-91%) versus 90% (95% CI, 89 to 91), but the 5-year OS increased from 92% (90%-94%) to 96% (95%-96%). In patients with intermediate prognosis, PFS remained similar with 75% (71%-79%) versus 78% (76%-80%) and the OS increased from 80% (76%-84%) to 89% (88%-91%). In patients with poor prognosis, the PFS increased from 41% (95% CI, 35 to 47) to 54% (95% CI, 52 to 56) and the OS from 48% (95% CI, 42 to 54) to 67% (95% CI, 65 to 69). A more granular prognostic model was developed and independently validated. This model identified a new cutoff of lactate dehydrogenase at a 2.5 upper limit of normal and increasing age and presence of lung metastases as additional adverse prognostic factors. An online calculator is provided (https://www.eortc.org/IGCCCG-Update). Conclusion: The IGCCCG Update model improves individual prognostication in metastatic nonseminomatous germ cell tumors. Increasing age and lung metastases add granularity to the original IGCCCG classification as adverse prognostic factors