Deriving a compound quality of life measure from the EORTC-QLQ-C30/LC13 instrument for use in economic evaluations of lung cancer clinical trials

Fluorouracil plasma monitoring: systematic review and economic evaluation of the My5-FU assay for guiding dose adjustment in patients receiving fluorouracil chemotherapy by continuous infusion

BACKGROUND

5-Fluorouracil (5-FU) is a chemotherapy used in colorectal, head and neck (H&N) and other cancers. Dose adjustment is based on body surface area (BSA) but wide variations occur. Pharmacokinetic (PK) dosing is suggested to bring plasma levels into the therapeutic range to promote fewer side effects and better patient outcomes. We investigated the clinical effectiveness and cost-effectiveness of the My5-FU assay for PK dose adjustment to 5-FU therapy.

OBJECTIVES

To systematically review the evidence on the accuracy of the My5-FU assay compared with gold standard methods [high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS)]; the effectiveness of My5-FU PK dosing compared with BSA; the effectiveness of HPLC and/or LC-MS compared with BSA; the generalisability of published My5-FU and PK studies; costs of using My5-FU; to develop a cost-effectiveness model.

DATA SOURCES

We searched MEDLINE, EMBASE, Science Citation Index and other databases between January and April 2014.

METHODS

Two reviewers independently screened titles and abstracts with arbitration and consensus agreement. We undertook quality assessment. We reconstructed Kaplan-Meier plots for progression-free survival (PFS) and overall survival (OS) for comparison of BSA and PK dosing. We developed a Markov model to compare My5-FU with BSA dosing which modelled PFS, OS and adverse events, using a 2-week cycle over a 20 year time horizon with a 3.5% discount rate. Health impacts were evaluated from the patient perspective, while costs were evaluated from the NHS and Personal Social Services perspective.

RESULTS

A total of 8341 records were identified through electronic searches and 35 and 54 studies were included in the clinical effectiveness and cost-effectiveness reviews respectively. There was a high apparent correlation between My5-FU, HPLC and LC-MS/mass spectrometer but upper and lower limits of agreement were -18% to 30%. Median OS were estimated as 19.6 [95% confidence interval (CI) 17.0 to 21.0] months for PK versus 14.6 (95% CI 14.1 to 15.3) months for BSA for 5-FU+folinic acid (FA); and 27.4 (95% CI 23.2 to 38.8) months for PK versus 20.6 (95% CI 18.4 to 22.9) months for BSA for FOLFOX6 in metastatic colorectal cancer (mCRC). PK versus BSA studies were generalisable to the relevant populations. We developed cost-effectiveness models for mCRC and H&N cancer. The base case assumed a cost per My5-FU assay of £ 61.03. For mCRC for 12 cycles of a oxaliplatin in combination with 5-fluorouracil and FA (FOLFOX) regimen, there was a quality-adjusted life-year (QALY) gain of 0.599 with an incremental cost-effectiveness ratio of £ 4148 per QALY. Probabilistic and scenario analyses gave similar results. The cost-effectiveness acceptability curve showed My5-FU to be 100% cost-effective at a threshold of £ 20,000 per QALY. For H&N cancer, again, given caveats about the poor evidence base, we also estimated that My5-FU is likely to be cost-effective at a threshold of £ 20,000 per QALY.

LIMITATIONS

Quality and quantity of evidence were very weak for PK versus BSA dosing for all cancers with no randomised controlled trials (RCTs) using current regimens. For H&N cancer, two studies of regimens no longer in use were identified.

CONCLUSIONS

Using a linked evidence approach, My5-FU appears to be cost-effective at a willingness to pay of £ 20,000 per QALY for both mCRC and H&N cancer. Considerable uncertainties remain about evidence quality and practical implementation. RCTs are needed of PK versus BSA dosing in relevant cancers.

Use of the lung cancer-specific Quality of Life Questionnaire EORTC QLQ-LC13 in clinical trials: A systematic review of the literature 20 years after its development

The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Lung Cancer 13 (QLQ-LC13) covers 13 typical symptoms of lung cancer patients and was the first module developed in conjunction with the EORTC core quality-of-life (QL) questionnaire. This review investigates how the module has been used and reported in cancer clinical trials in the 20 years since its publication. Thirty-six databases were searched with a prespecified algorithm. This search plus an additional hand search generated 770 hits, 240 of which were clinical studies. Two raters extracted data using a coding scheme. Analyses focused on the randomized controlled trials (RCTs). Of the 240 clinical studies that were identified using the LC13, 109 (45%) were RCTs. More than half of the RCTs were phase 3 trials (n = 58). Twenty RCTs considered QL as the primary endpoint, and 68 considered it as a secondary endpoint. QL results were addressed in the results section of the article (n = 89) or in the abstract (n = 92); and, in half of the articles, QL results were presented in the form of tables (n = 53) or figures (n = 43). Furthermore, QL results had an impact on the evaluation of the therapy that could be clearly demonstrated in the 47 RCTs that yielded QL differences between treatment and control groups. The EORTC QLQ-LC13 fulfilled its mission to be used as a standard instrument in lung cancer clinical trials. An update of the LC13 is underway to keep up with new therapeutic trends and to ensure optimized and relevant QL assessment in future trials.

A patient-based utility measure of health for clinical trials of cancer therapy based on the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire

BACKGROUND

The European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30) is a widely used quality-of-life measure in oncology. The ability to translate QLQ-C30 responses into utility scores would further expand its use in medical decision-making. The aims of this study were to: 1) map QLQ-C30 responses onto patient time trade-off utility scores; and 2) compare a multiattribute approach to a global evaluation approach to modeling utility scores.

METHODS

Two distinct approaches were applied to data from 1432 cancer patients. The multiattribute approach used psychometric analysis and expert input to select a subset of functioning and symptom scale items for modeling. The second approach focused on global health and quality-of-life items based on a conceptual model. Model selection criteria included parsimony, statistical significance and logical consistency of parameter estimates, predictive accuracy, number of states described, and scale range.

RESULTS

The optimal multiattribute model included nine variables for five items from different scales, described 144 unique states, predicted values ranging from 0.63 to 1.00, but it had poor predictive accuracy (cross-validation pseudo-R(2) = 0.056). The best-fitting global approach-based model described 24 unique states using eight indicators for two items from one scale (plus a constant) and predicted values ranging from 0.17 to 1.00 (cross-validation pseudo-R(2) = 0.127).

CONCLUSIONS

Multiattribute models produced a greater number of unique predicted values, while global models exhibited more desirable statistical properties and a wider range of values. The recommended models will enable users to predict cancer patients' utilities from existing and future QLQ-C30 data sets.

A dynamic model for estimating changes in health status and costs

We develop an innovative method to assess total treatment costs over a finite period of time while incorporating the dynamics of change in the health status of patients. Costs are incurred through medical care use while patients sojourn in health states. Because complete ascertainment of costs and observation of events are not always feasible, some patient utilization will be incomplete and events will also be censored. A Markov model is used to estimate the transition probabilities between health states and the impact of patient variables on transition intensities. A mixed-effects model is used for sojourn costs with transition times as random effects and patient variables as fixed effects. The models are combined to estimate net present values (NPVs) of expenditures over a finite time interval as a function of patient characteristics. The method is applied to a data set of 624 incident cases of cancer. Physical functioning after cancer diagnosis was assessed periodically through structured interviews. The outcomes of interest are normal physical function, impaired physical function, or the terminal state, dead. Charges were obtained from Medicare claim files for 2 years following cancer diagnosis. For demonstration purposes, we estimate NPVs for charges incurred over 2 years by cancer site and cancer stage. Our method, a joint regression model, provides a flexible approach to assessing the influence of patient characteristics on both cost and health outcomes while accommodating heteroscedasticity, skewness and censoring in the data.

Eliciting social preference weights for Functional Assessment of Cancer Therapy-Lung health states

BACKGROUND

The Functional Assessment of Cancer Therapy-Lung (FACT-L) is a multidimensional measure of quality of life developed for use in the evaluation of interventions in lung cancer.

OBJECTIVE

To develop a set of utility weights that could be used to convert FACT-L into a single index capable of being used in the economic analysis of clinical trial data.

METHOD

A core set of FACT-L items were valued in two versions of a 14-page postal survey of over 400 members of the UK general population. Respondents valued hypothetical FACT-L health states using a scale from 0 to 100 (worst to best health state). Respondents also valued their own health using the standard form of the EuroQol EQ-5D. Data were entered into an ordinary least squares regression model.

RESULTS

Item weights estimated in regression analysis yielded values for 10 items from the FACT-L. The summary index based on this selected set of FACT-L items has a maximum value of 0.703 and a minimum value of 0.111.

CONCLUSION

This study demonstrates a practical method of converting a standard condition-specific measure into a form that has the requisite properties to legitimise its use in cost-utility analysis. The methodology used here is not unique to FACT-L and might be considered appropriate for use in converting similar instruments.