How strongly is progression-free survival (PFS) associated with health-related quality of life (HRQoL) in studies of cancer treatments?
This systematic review and quantitative analysis of 52 articles reporting on 38 randomized clinical cancer trials did not find a significant association between PFS and HRQoL.
These findings raise questions about the assumption that interventions prolonging PFS also improve HRQoL in patients with cancer and suggest that HRQoL should be measured directly and accurately, with adequate follow-up time, in future studies.
Progression-free survival (PFS) has become a commonly used outcome to assess the efficacy of new cancer drugs. However, it is not clear if delay in progression leads to improved quality of life with or without overall survival benefit.
To evaluate the association between PFS and health-related quality of life (HRQoL) in oncology through a systematic review and quantitative analysis of published randomized clinical trials. Eligible trials addressed oral, intravenous, intraperitoneal, or intrapleural chemotherapy or biological treatments, and reported PFS or health-related quality of life.
For this systematic review and quantitative analysis of randomized clinical trials of patients with cancer, we searched Medline, Embase, and the Cochrane Central Register of Controlled Trials from January 1, 2000, through May 4, 2016.
Paired reviewers independently screened citations, extracted data, and assessed risk of bias of included studies.
Data Extraction and Synthesis
We examined the association of difference in median PFS duration (in months) between treatment groups with difference in global, physical, and emotional HRQoL scores between groups (standardized to a range of 0-100, with higher scores representing better HRQoL) using weighted simple regressions.
Main Outcome and Measure
The association between PFS duration and HRQoL.
Of 35 960 records screened, 52 articles reporting on 38 randomized clinical trials involving 13 979 patients across 12 cancer types using 6 different HRQoL instruments were included. The mean (SD) difference in median PFS between the intervention and the control arms was 1.91 (3.35) months. The mean (SD) differences in change of HRQoL adjusted to per-month values were −0.39 (3.59) for the global domain, 0.26 (5.56) for the physical domain, and 1.08 (3.49) for the emotional domain. The slope of the association between the difference in median PFS and the difference in change for global HRQoL (n = 30 trials) was 0.12 (95% CI, −0.27 to 0.52); for physical HRQoL (n = 20 trials) it was −0.20 (95% CI, −0.62 to 0.23); and for emotional HRQoL (n = 13 trials) it was 0.78 (95% CI, −0.05 to 1.60).
Conclusions and Relevance
We failed to find a significant association between PFS and HRQoL in cancer clinical trials. These findings raise questions regarding the assumption that interventions prolonging PFS also improve HRQoL in patients with cancer. Therefore, to ensure that patients are truly obtaining important benefit from cancer therapies, clinical trial investigators should measure HRQoL directly and accurately, ensuring adequate duration and follow-up.
The goal of patient-centered cancer care is to extend survival or improve health-related quality of life (HRQoL).1-3 Patients, clinicians, and investigators value overall survival (OS), an objective end point representing survival duration, as the most important cancer trial outcome.3,4 However, HRQoL, which reflects patients’ subjective feelings about their health,1,3 is also important, and represents a research priority for the American Society of Clinical Oncology.1 Although important benefit should ultimately be established by improved OS and HRQoL, regulatory authorities have also approved cancer treatments on the basis of surrogates such as progression-free survival (PFS)3 or time to progression (TTP).5
Originally developed as a measurement tool to identify signals of activity in early drug development,2 PFS has become a widely used surrogate outcome in cancer. The appeal of PFS use in randomized clinical trials (RCTs)2 reflects limitations associated with OS,2,3,5 including higher cost, longer follow-up, larger sample sizes, and confounding effects arising from crossover designs and subsequent postprogression therapies. The increasing use of PFS is also reflected in drug regulatory approvals,2 with at least a dozen drugs approved by the US Food and Drug Administration (FDA) between 2005 and 2010 using PFS as primary end point.6
There are only 2 reasons to use PFS as a valid end point in oncology. The first reason is the belief that PFS is a valid surrogate marker for OS. The second reason is the assumption that patients who live longer without disease progression will have better HRQoL, even without longer survival. However, valid surrogate end points should reliably and precisely predict treatment effect on the corresponding patient-important outcome, either survival or how a patient feels or functions.6 This definition is currently implemented by regulatory agencies that grant oncology drugs either accelerated or traditional marketing approvals (eg, the FDA).7 Currently, evidence suggests that PFS serves as a valid surrogate for OS only in limited scenarios, being both variable and unpredictable.2,6,8 Additionally, because HRQoL is likely to be impaired by adverse events (AEs) resulting from the treatments responsible for prolonged PFS, its association with improved HRQoL is far from self-evident.5 These uncertainties have led oncological experts to raise concerns regarding the appropriateness of using PFS as a primary outcome for evaluating new treatments,1,2,5 suggesting that the convenience of shorter and smaller trials made possible by measuring PFS is driving its use, rather than compelling evidence of its adequate surrogacy for either OS or HRQoL.2
Because few studies measure the value or benefits of PFS for patients, and few trials collect and report HRQoL data,5,9 resolving the question of PFS as a satisfactory surrogate for HRQoL is challenging. To our knowledge, there exists only 1 systematic analysis of the PFS-HRQoL association, and that study yielded inconclusive results.6
Given the increased use of PFS as the primary outcome in new oncology drug trials, and uncertain surrogacy of PFS for either OS or HRQoL, it remains possible that patients are receiving toxic and/or expensive treatments without experiencing important benefit, and an examination of evidence regarding whether delay in progression leads to better HRQoL is critical. We have therefore examined the PFS-HRQoL association through a systematic review and quantitative analysis of published studies of oral, intravenous, intraperitoneal, or intrapleural chemotherapy or biological therapy designed to improve disease-related outcomes among patients with cancer in RCT settings.
Our study protocol detailing design and analysis was previously published10 and registered on the International Prospective Register of Ongoing Systematic Reviews (CRD42016047162).11,12 We conducted a review of human cancer RCTs published from January 1, 2000, to May 4, 2016, using standard methodology described by the Cochrane Collaboration.13 Our systematic review adheres to PRISMA Statement14,15 guidelines ensuring transparent and complete reporting. We included trials reporting on PFS outcome estimates and HRQoL measures with chemotherapy and/or biological type cancer therapies as the primary investigational anticancer treatment. Randomized clinical trials with OS benefit were excluded from the original protocol but were included in the final analysis. We used the global HRQoL domain score in the final base-case analysis as opposed to the physical domain score in the original protocol. Changes to the original protocol were made as a response to comments received during the peer-review process.
We used comprehensive search strategies developed with help from an experienced research librarian (eAppendix in the Supplement).10 We used the OVID platform to search in MEDLINE, Embase, and the Wiley Cochrane databases, and used MeSH terms and free text to capture RCTs published in Abridged Index Medicus.16 Our search strategies were built by combining terms from disease key areas (cancer categories), HRQoL, cancer therapies, and an RCT filter. To increase comprehensiveness, we included a list of drugs approved by the FDA based on PFS benefit,6 and set no language limitations. We used a previous report6 to preidentify key articles eligible for review, and performed search strategy validation check through verification of inclusion of key articles in search results. All references were managed using EndNoteX version 7.0.2 (Thomson Reuters).
Study Screening and Data Abstraction
Ten pairs of reviewers working independently conducted eligibility screening and data abstraction. The international team allowed for article screening and abstraction in multiple languages, reducing language limitations. Reviewers resolved disagreement by either discussion or adjudication by an arbitrator (B.K.).
Screening was performed using pilot-tested electronic forms in DistillerSR (Evidence Partners), constructed per eligibility criteria.10 Reviewers received training and detailed written instructions to perform title and abstract and full-text screening, including meetings with calibration and sample data review exercises. We measured reviewer agreement on full-text screening using Kappa (κ), per guidelines proposed by Landis and Koch,17 by using the VassarStats Kappa online calculator.18
Oncology trials often report PFS results first and subsequently separately publish HRQoL results. Therefore, we classified trial publications into 3 categories of outcome reporting: (1) only PFS outcome data (ie, typical oncology trial publication), (2) only HRQoL data, or (3) publications reporting PFS and HRQoL. Because all categories of publications are potentially relevant, we performed trial-level publication matching and searching prior to data abstraction for publications reporting only PFS or HRQoL. We first cross-referenced categorized publication types against each other (ie, trial-level matching) for eligible full-text articles to identify and capture trials reporting required data across multiple publications. Furthermore, we performed additional supplemental searches through OVID for additional unmatched publications using author, intervention, and cancer type keywords in the MEDLINE and Embase databases.
For data abstraction, reviewers underwent similar training and calibration as for screening, and undertook abstraction using pilot-tested electronic forms in Microsoft Excel software. Data abstraction included PFS and HRQoL information for median PFS time and/or PFS hazard ratios (HRs) for intervention and control groups, HRQoL scores and corresponding error estimates for global domain, time of each successive HRQoL measurement in each group, and sample size at each HRQoL measurement point. We also abstracted physical and emotional HRQoL domain scores to conduct sensitivity analyses. Additional data originally intended for further sensitivity and subgroup analyses (ie, risk of bias, cancer types and stages, industry funding) within each HRQoL domain were abstracted10; however, an insufficient number of trials within each HRQoL domain precluded these analyses.
All included trials reported median progression times for intervention and control groups, and we calculated incremental PFS for each study by taking difference in median PFS duration between arms. Although PFS includes death, while TTP does not, approximately 25% of trials (10 of 38) used TTP, so we assumed TTP to be equal to PFS, since most trials reported PFS.
Although per-trial instrument selection had no effect on calculation of HRQoL scores owing to score standardization, we established a hierarchy of measures, using the highest in the hierarchy for our analyses as follows: FACT-G,19 then the EORTC-QLQ-C30,20,21 and finally any other instrument available. All HRQoL scores across instruments were standardized to the scale from 0 to 100, with higher scores representing better HRQoL. In each arm, HRQoL for the duration of provided measures was calculated by using an area under the curve (AUC) approach, adjusting for different durations in measuring and/or reporting HRQoL between arms. Then incremental HRQoL was calculated as the difference in the AUC between 2 arms, adjusted to per-month values. This served to reduce overall heterogeneity of the y-axis by reducing variability due to differences in HRQoL time durations across trials, and it allowed for facilitated visual comparison of relative HRQoL benefits across trials in constructed PFS-HRQoL scatterplots (eAppendix in the Supplement).
Global HRQoL domain scores were used for the base case analysis, since global scores were reported most often. The physical and emotional HRQoL domain scores from each trial were used in sensitivity analyses to maximize comparability across cancer types by using these commonly measured specific domains of perceived importance.
We constructed a scatterplot of incremental HRQoL (y-axis) vs incremental PFS (x-axis), with each study point representing an individual trial. To estimate the PFS-HRQoL association, we used weighted simple regression to calculate the slope (regression coefficient) between PFS and HRQoL domains. To account for different sample sizes across studies, each study point in the regression was weighted by the inverse of total variance.
All analyses were conducted using Microsoft Excel and SPSS software (version 22). The eAppendix in the Supplement of the present report and the eAppendix in the Supplement of our protocol provide a detailed description of the methods for our analyses.10
We initially identified 35 960 citations in the MEDLINE, Embase, and Cochrane databases, with a total of 30 294 articles after duplicate removal. We removed 27 943 articles after title and abstract screening, leaving 2351 full-text articles assessed for eligibility, with 2307 being excluded. In addition to the 44 articles finally identified in the primary search, we included 8 more articles identified through a supplemental search on the trials that reported OS benefits. Finally, our review included a total of 38 trials reported in 52 articles.22-73Figure 1 presents the article selection process.74 We calculated that κ = 0.75 (95% CI, 0.73-0.78) indicated substantial agreement17 between reviewers in assessments of study inclusion during full-text screening.
Of the 52 articles representing 38 trials, 24 reported both PFS and HRQoL data in a single article. Trial-level matching and searching identified another 28 articles representing 14 eligible RCTs. In relation to the low number of finally eligible articles, it is worth noting that although cancer trials might measure HRQoL, many of these trials fail to publish or report their HRQoL data to allow for the quantitative analyses, resulting in these being excluded from our analysis according to our eligibility criteria.
The 30 294 potentially eligible articles included 1607 non-English language publications (in Chinese, French, German, Japanese, Korean, Polish, and Spanish). Three Chinese articles,35,60,66 the largest non-English language group, were finally included in our quantitative synthesis.
Table 1 details the trial characteristics organized alphabetically by cancer type, with Trial ID format corresponding to the specific cancer type (abbreviated by a single or double letter) and trial number for each type. A plus sign set at the end of the Trial ID indicates that the trial found statistically significant OS benefits.
The 38 eligible trials, published between 2000 and 2016, involved 13 979 patients across 12 cancer types. Nine cancer types were studied in multiple trials. Trials enrolled from 40 to 1253 adult patients aged 18 to 93 years. Intervention treatments varied widely, both across and within cancer types. The variability of comparators was lower, with some repetition within cancer type. Reported median follow-up ranged from 10.5 to 66.0 months across trials. Median PFS of trial interventions ranged from 1.8 to 33.7 months, and the duration of reported or measured HRQoL ranged from 1 to 34 months. Of the 38 trials, 24 had shorter HRQoL follow-up than median PFS for the intervention. The HRQoL instrument completion rates from baseline to last measurement for global, physical, or emotional (reported in this order—depending on availability) ranged across trials from 13% to 100% completion. The 38 studies included in our analysis used 6 different HRQoL instruments: 19 trials used the EORTC-QLQ-C3020,21; 13 used the FACT-G19; 3 used the Lung Cancer Symptom Scale75; and 1 each used the EQ-5D,76 the 8-item linear analog self-assessment (LASA) questionnaire,77 and clinician-reported Karnofsky score.78 Of the 38 trials, 32 (84%) had high risk of bias in at least 1 of 4 domains (ie, loss to follow-up, failure to follow up with patients after progression, absence of blinding in participants or study personnel, or outcome assessment),10 with 16 of 38 trials failing to follow up with patients after progression.
Table 2 details the study data results used in our regression analyses. Of the 38 trials, 28 (74%) reported improved PFS for intervention vs comparator. The mean (SD) difference in median PFS between the intervention and the control arms was 1.91 months (3.35). Global HRQoL was the most common domain, reported in 30 of 38 trials (79%), followed by physical HRQoL reported in 20 of 38 trials (53%), while emotional HRQoL was reported in 13 of 38 RCTs (34%). Of the RCTs reporting HRQoL across the different domains, 16 of 30 (53%), 11 of 20 (55%), and 8 of 13 (62%) trials demonstrated improved global, physical, and emotional HRQoL, respectively, for the intervention vs the comparator. The mean (SD) incremental HRQoL adjusted to per-month values were −0.39 (3.59) for the global domain, 0.26 (5.56) for the physical domain, and 1.08 (3.49) for the emotional domain.
Figure 2 presents scatterplots of the relationship between PFS and each of the HRQoL domains. The slope of the association between the difference in median PFS and the difference in change for global HRQoL (n = 30 trials) was 0.12 (95% CI, −0.27 to 0.52); for physical HRQoL (n = 20 trials), −0.20 (95% CI, −0.62 to 0.23); and for emotional HRQoL (n = 13 trials), 0.78 (95% CI, −0.05 to 1.60).
It became clear after graphing Figure 2A and B (global and physical HRQoL, respectively) that trial MM1 was an outlier, so we used deletion diagnostics to assess the magnitude of influence on the regression coefficients. After MM1 was removed from analysis, the new global HRQoL slope was 0.28 (95% CI, −0.50 to 1.05), and the new physical HRQoL slope was −0.30 (95% CI, −1.30 to 0.70). The level of outlier influence on the main analyses, therefore, seemed to be low, since the deletion of this data point did not change the overall conclusions found.
We performed a systematic review and quantitative analysis of published RCTs, and estimated the PFS-HRQoL association using simple regression to calculate the slope between PFS and HRQoL. Our review and analysis failed to find a significant association between any of the 3 HRQoL domains and PFS. We noted that there was no consistent PFS-HRQoL directional association with similar regression coefficient confidence interval results across the 3 HRQoL domains.
To our knowledge, the question of PFS-HRQoL association in oncology has been examined in only 1 previous study, by the Agency for Healthcare Research and Quality.6 Since this study chose to include only studies with a direct quantitative statistical comparison of PFS with HRQoL, there was limited comprehensiveness, resulting in the inclusion of only 4 studies, and inconclusive findings.
The increasing use of PFS as an end point in oncology RCTs and as a criterion for drug regulatory approvals over recent years has been based 2 practical advantages of using PFS over OS to evaluate drugs: (1) lower requirements for both sample size and extended follow-up, and thus greater speed of trial completion; and (2) a reduction in confounding by crossover designs and subsequent postprogression therapies. In addition to these practical advantages, PFS advocates believe that PFS indicates disease control and stabilization, leading to reduction in disease symptoms, thus implying clinical benefit through improvement in HRQoL.6,9 Our results cast doubts on such assumptions.
These results have important implications for the design and conduct of oncology RCTs. One possible conclusion is that trials with a primary PFS end point also need to be designed to provide high-quality findings regarding whether the interventions affect HRQoL, including adequate power and data quality (duration of follow-up and high patient compliance). This approach will avoid assumptions79 and would make the relationship between PFS outcomes and HRQoL outcomes clear, allowing clinical judgment to assess benefits vs risks should the HRQoL outcomes be compromised by treatments that increase PFS. In contrast to the solution for the apparent inadequacy of PFS as a surrogate by ensuring trials are powered to definitively establish effect on OS, ensuring that results demonstrate the effect on HRQoL may not require larger studies. Oncology-specific instruments are responsive to small but important changes in HRQoL80,81 and may require sample sizes of the same order as those powered to establish PFS. Our finding of approximately the same proportion of trials showing HRQoL benefit as those showing PFS benefit supports this observation.
The necessary measurement of HRQoL in RCTs will come with logistical challenges. Investigators will have to implement strategies to minimize the missing HRQoL data, a frequent problem in current RCTs that address HRQoL. Such strategies would include requiring baseline measurement of HRQoL prior to randomization into trials,82,83 careful monitoring to ensure that measurement takes place at each patient visit, obtaining contact information for a number of individuals with whom patients are not living but who are likely to be aware of their whereabouts, ensuring that resources are available for tracking patients who prove hard to follow, and using electronic administration of HRQoL instruments completed by patients themselves. Furthermore, investigators will have to ensure adequate logistical planning and institutional staff training that will further minimize missing data and ensure optimal administration of HRQoL instruments.6,83-85
Strengths and Limitations
The present study, which quantitatively evaluates the PFS-HRQoL association in oncology, has several strengths. First, we conducted an exhaustive search with no language limitations. Second, we developed explicit eligibility criteria and conducted duplicate assessment of eligibility and data abstraction that included use of standardized and pilot-tested screening and data abstraction forms, review team meetings, and communications to ensure resolution of reviewer concerns. As a result, excellent agreement between raters was achieved. Third, we developed a quantitative analysis methodology that allowed inclusion of the widest possible range of relevant publications. Finally, our trial data set had widely distributed patient and trial characteristics, ensuring optimally generalizable results.
The study also has limitations. First, since more than 60% of the trials had shorter HRQoL follow-up than median PFS for the interventions, and 16 of the 38 trials failed to follow up with patients after progression, we may not have captured some HRQoL benefit attributable to PFS that could have occurred later, and thus our findings may underestimate the association between PFS and HRQoL. Second, a large proportion of the included studies (24 of 38) involved traditional cytotoxic chemotherapeutic agents, and since different correlations may exist based on therapy class, our results are potentially more applicable to cytotoxic agents. Third, our failure to show an association could be a result of a lack of statistical power arising from the limited number of trials included in the analysis. For example, the magnitude of the association for the emotional domain was relatively large, but its statistical nonsignificance might be due to the small number of trials reported this domain score. Fourth, with only 38 eligible RCTs, we could not perform some planned sensitivity and subgroup analyses, and there may therefore be subgroups in which the association is stronger than the overall evidence suggests.
The present systematic review and quantitative analysis failed to find a significant association between PFS and HRQoL in oncology RCTs. This finding challenges the use of PFS as the primary efficacy end point in oncology trials. The results suggest that optimally meeting the needs of cancer patients requires trials that are adequately powered for OS, and/or designed to ensure rigorous and trustworthy measurement of HRQoL.
Accepted for Publication: July 22, 2018.
Corresponding Author: Feng Xie, PhD, Programs for Health Economics and Outcome Measures, Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, Centre for Health Economics and Policy Analysis, McMaster University, CRL-223 1280 Main St W, Hamilton, ON L8S 4K1, Canada (email@example.com).
Published Online: October 1, 2018. doi:10.1001/jamainternmed.2018.4710
Author Contributions: Dr Kovic had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Kovic, Kennedy, Gomaa, Thabane, Brundage, Guyatt, F. Xie.
Acquisition, analysis, or interpretation of data: Kovic, Jin, Kennedy, Hylands, Pędziwiatr, Kuriyama, Lee, Katsura, Tada, B. Hong, Cho, P. Hong, Yu, Sivji, Toma, L. Xie, Tsoi, Waligora, Prasad, Bhatnagar, Thabane, Brundage, Guyatt, F. Xie.
Drafting of the manuscript: Kovic, Kennedy, Gomaa, B. Hong, Tsoi, F. Xie.
Critical revision of the manuscript for important intellectual content: Kovic, Jin, Kennedy, Hylands, Pędziwiatr, Kuriyama, Lee, Katsura, Tada, B. Hong, Cho, P. Hong, Yu, Sivji, Toma, L. Xie, Waligora, Prasad, Bhatnagar, Thabane, Brundage, Guyatt, F. Xie.
Statistical analysis: Kovic, Cho, Prasad, Thabane, F. Xie.
Obtained funding: F. Xie.
Administrative, technical, or material support: Kovic, Jin, Kennedy, Hylands, Gomaa, Lee, Katsura, B. Hong, P. Hong, L. Xie, Tsoi, Bhatnagar, F. Xie.
Study supervision: Thabane, Brundage, Guyatt, F. Xie.
Conflict of Interest Disclosures: None reported.
Funding/Support: Dr Waligora was funded by the National Science Centre (NCN) in Poland under grant UMO-2015/18/E/HS1/00354.
Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: We thank Maria Cecilia Arechabala, MSc, for her assistance with citation screening, Nora (Zhiyuan) Chen, MSc, for her assistance with literature searching and article retrieval, as well as Daniel Shi, BHSc, Leon Li, BHSc, Kailai (Kevin) Zhang, BHSc, and Valerie (Seungyeon) Kim, BHSc, for their assistance with article retrieval. We also thank Oren Levin, MD, for reviewing our manuscript to improve its readability. They received no compensation for their contributions.
Additional Information: Sections of this article also appear in Dr Kovic’s PhD thesis.
et al; American Society of Clinical Oncology. American Society of Clinical Oncology statement: toward individualized care for patients with advanced cancer. J Clin Oncol
. 2011;29(6):755-760. doi:10.1200/JCO.2010.33.1744PubMedGoogle ScholarCrossref
et al. Progression-Free Survival: What Does It Mean for Psychological Well-Being or Quality of Life? Rockville, MD: Agency for Healthcare Research and Quality; 2013.
V. Strength of Validation for Surrogate End Points Used in the US Food and Drug Administration’s Approval of Oncology Drugs. Mayo Clin Proc
. 2016;S0025-6196(16)00125-7.PubMedGoogle Scholar
AS. A comparison of response patterns for progression-free survival and overall survival following treatment for cancer with PD-1 inhibitors: a meta-analysis of correlation and differences in effect sizes. JAMA Netw Open
. 2018;1(2):e180416. doi:10.1001/jamanetworkopen.2018.0416Google ScholarCrossref
et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ
. 2009;339:b2700. doi:10.1136/bmj.b2700PubMedGoogle ScholarCrossref
et al. The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst
. 1993;85(5):365-376. doi:10.1093/jnci/85.5.365PubMedGoogle ScholarCrossref
et al. Choosing between the EORTC QLQ-C30 and FACT-G for measuring health-related quality of life in cancer clinical research: issues, evidence and recommendations. Ann Oncol
. 2011;22(10):2179-2190. doi:10.1093/annonc/mdq721PubMedGoogle ScholarCrossref
et al. Doxorubicin and paclitaxel versus doxorubicin and cyclophosphamide as first-line chemotherapy in metastatic breast cancer: the European Organization for Research and Treatment of Cancer 10961 Multicenter Phase III Trial. J Clin Oncol
. 2002;20(14):3114-3121. doi:10.1200/JCO.2002.11.005PubMedGoogle ScholarCrossref
et al; European Organization for Research and Treatment of Cancer Breast Cancer Group. Randomized, controlled trial investigating short-term health-related quality of life with doxorubicin and paclitaxel versus doxorubicin and cyclophosphamide as first-line chemotherapy in patients with metastatic breast cancer: European Organization for Research and Treatment of Cancer Breast Cancer Group, Investigational Drug Branch for Breast Cancer and the New Drug Development Group Study. J Clin Oncol
. 2004;22(13):2576-2586. doi:10.1200/JCO.2004.02.037PubMedGoogle ScholarCrossref
et al; European Organisation for Research and Treatment of Cancer Breast Cancer Group; National Cancer Institute of Canada; Swiss Group for Clinical Cancer Research. Health-related quality of life in survivors of locally advanced breast cancer: an international randomised controlled phase III trial. Lancet Oncol
. 2005;6(5):287-294. doi:10.1016/S1470-2045(05)70100-5PubMedGoogle ScholarCrossref
et al. A phase III randomized comparison of lapatinib plus capecitabine versus capecitabine alone in women with advanced breast cancer that has progressed on trastuzumab: updated efficacy and biomarker analyses. Breast Cancer Res Treat
. 2008;112(3):533-543. doi:10.1007/s10549-007-9885-0PubMedGoogle ScholarCrossref
et al. Phase III, double-blind, randomized study comparing lapatinib plus paclitaxel with placebo plus paclitaxel as first-line treatment for metastatic breast cancer. J Clin Oncol
. 2008;26(34):5544-5552. doi:10.1200/JCO.2008.16.2578PubMedGoogle ScholarCrossref
B, Di Leo
et al. Quality-of-life and quality-adjusted survival (Q-TWiST) in patients receiving lapatinib in combination with paclitaxel as first-line treatment for metastatic breast cancer. Curr Med Res Opin
. 2010;26(4):767-775. doi:10.1185/03007991003590860PubMedGoogle ScholarCrossref
et al. Effects on quality of life of weekly docetaxel-based chemotherapy in patients with locally advanced or metastatic breast cancer: results of a single-centre randomized phase 3 trial. BMC Cancer
. 2011;11:75. doi:10.1186/1471-2407-11-75PubMedGoogle ScholarCrossref
et al; Southern Italy Cooperative Oncology Group. Randomised trial comparing biweekly oxaliplatin plus oral capecitabine versus oxaliplatin plus IV bolus fluorouracil/leucovorin in metastatic colorectal cancer patients: results of the Southern Italy Cooperative Oncology study 0401. J Cancer Res Clin Oncol
. 2009;135(2):217-226. doi:10.1007/s00432-008-0454-7PubMedGoogle ScholarCrossref
et al. Quality of life and disease-related symptoms in previously treated Japanese patients with non-small-cell lung cancer: results of a randomized phase III study (V-15-32) of gefitinib versus docetaxel. Ann Oncol
. 2009;20(9):1483-1488. doi:10.1093/annonc/mdp031PubMedGoogle ScholarCrossref
et al. A multicenter, randomized, double-blind, placebo-controlled safety study to evaluate the clinical effects and quality of life of paclitaxel-carboplatin (PC) alone or combined with endostar for advanced non-small cell lung cancer (NSCLC) [in Chinese]. Zhonghua Zhong Liu Za Zhi
. 2011;33(11):854-859.PubMedGoogle Scholar
et al; Korean Cancer Study Group. Gefitinib versus pemetrexed as second-line treatment in patients with nonsmall cell lung cancer previously treated with platinum-based chemotherapy (KCSG-LU08-01): an open-label, phase 3 trial. Cancer
. 2012;118(24):6234-6242. doi:10.1002/cncr.27630PubMedGoogle ScholarCrossref
MR. Health-related quality of life in patients with advanced metastatic melanoma: results of a randomized phase III study comparing temozolomide with dacarbazine. Cancer Invest
. 2003;21(6):821-829. doi:10.1081/CNV-120025084PubMedGoogle ScholarCrossref
et al. Patient perception of the benefit of a BRAF inhibitor in metastatic melanoma: quality-of-life analyses of the BREAK-3 study comparing dabrafenib with dacarbazine. Ann Oncol
. 2014;25(7):1428-1436. doi:10.1093/annonc/mdu154PubMedGoogle ScholarCrossref
et al. Lenalidomide, melphalan, and prednisone, followed by lenalidomide maintenance, improves health-related quality of life in newly diagnosed multiple myeloma patients aged 65 years or older: results of a randomized phase III trial. Haematologica
. 2013;98(5):784-788. doi:10.3324/haematol.2012.074534PubMedGoogle ScholarCrossref
et al; Arbeitsgemeinschaft Gynäkologische Onkologie Ovarian Cancer Study Group. A randomized clinical trial of cisplatin/paclitaxel versus carboplatin/paclitaxel as first-line treatment of ovarian cancer. J Natl Cancer Inst
. 2003;95(17):1320-1329. doi:10.1093/jnci/djg036PubMedGoogle ScholarCrossref
et al. Pegylated liposomal doxorubicin and carboplatin compared with paclitaxel and carboplatin for patients with platinum-sensitive ovarian cancer in late relapse. J Clin Oncol
. 2010;28(20):3323-3329. doi:10.1200/JCO.2009.25.7519PubMedGoogle ScholarCrossref
et al. Patient-reported outcomes in relapsed ovarian cancer: results from a randomized Phase III study of trabectedin with pegylated liposomal doxorubicin (PLD) versus PLD alone. Gynecol Oncol
. 2012;127(1):161-167. doi:10.1016/j.ygyno.2012.06.034PubMedGoogle ScholarCrossref
et al. Health-related quality of life outcomes of docetaxel/carboplatin combination therapy vs. sequential therapy with docetaxel then carboplatin in patients with relapsed, platinum-sensitive ovarian cancer: results from a randomized clinical trial. Gynecol Oncol
. 2011;123(3):505-510. doi:10.1016/j.ygyno.2011.08.015PubMedGoogle ScholarCrossref
et al. Patient reported outcomes of a randomized, placebo-controlled trial of bevacizumab in the front-line treatment of ovarian cancer: a Gynecologic Oncology Group Study. Gynecol Oncol
. 2013;128(3):573-578. doi:10.1016/j.ygyno.2012.11.038PubMedGoogle ScholarCrossref
et al. Phase III study comparing gemcitabine plus cetuximab versus gemcitabine in patients with advanced pancreatic adenocarcinoma: Southwest Oncology Group-directed intergroup trial S0205. J Clin Oncol
. 2010;28(22):3605-3610. doi:10.1200/JCO.2009.25.7550PubMedGoogle ScholarCrossref
et al. Pain and emotional well-being outcomes in Southwest Oncology Group-directed intergroup trial S0205: a phase III study comparing gemcitabine plus cetuximab versus gemcitabine as first-line therapy in patients with advanced pancreas cancer. J Clin Oncol
. 2010;28(22):3611-3616. doi:10.1200/JCO.2009.25.8285PubMedGoogle ScholarCrossref
et al. Randomized study of three different doses of suramin administered with a fixed dosing schedule in patients with advanced prostate cancer: results of intergroup 0159, cancer and leukemia group B 9480. J Clin Oncol
. 2002;20(16):3369-3375. doi:10.1200/JCO.2002.10.022PubMedGoogle ScholarCrossref
et al; Cancer and Leukemia Group B. Quality of life impact of three different doses of suramin in patients with metastatic hormone-refractory prostate carcinoma: results of Intergroup O159/Cancer and Leukemia Group B 9480. Cancer
. 2004;101(10):2202-2208. doi:10.1002/cncr.20655PubMedGoogle ScholarCrossref
N. Health-related quality of life in pain-free or mildly symptomatic patients with metastatic hormone-resistant prostate cancer following treatment with the specific endothelin A receptor antagonist zibotentan (ZD4054). J Cancer Res Clin Oncol
. 2011;137(1):99-113. doi:10.1007/s00432-010-0864-1PubMedGoogle ScholarCrossref
et al. The feasibility of triple-drug chemotherapy combination in older adult patients with oesophagogastric cancer: a randomised trial of the Arbeitsgemeinschaft Internistische Onkologie (FLOT65+). Eur J Cancer
. 2013;49(4):835-842. doi:10.1016/j.ejca.2012.09.025PubMedGoogle ScholarCrossref
et al; FFCD (Fédération Francophone de Cancérologie Digestive). Longitudinal quality of life study in patients with metastatic gastric cancer: analysis modalities and clinical applicability of QoL in randomized phase II trial in a digestive oncology. Gastroenterol Clin Biol
. 2005;29(11):1113-1124. doi:10.1016/S0399-8320(05)82175-XPubMedGoogle ScholarCrossref
B. Clinical observation on recombinant human vascular endostatin combined with XELOX regimen in the treatment of advanced stomach carcinoma. [in Chinese]. Tumor
. 2009;29(8):790-792.Google Scholar
et al; Gynecologic Oncology Group. Clinical results and quality of life analysis for the MVAC combination (methotrexate, vinblastine, doxorubicin, and cisplatin) in carcinoma of the uterine cervix: a Gynecologic Oncology Group study. Gynecol Oncol
. 2006;100(3):537-543. doi:10.1016/j.ygyno.2005.09.023PubMedGoogle ScholarCrossref
et al. Phase III trial of four cisplatin-containing doublet combinations in stage IVB, recurrent, or persistent cervical carcinoma: a Gynecologic Oncology Group study. J Clin Oncol
. 2009;27(28):4649-4655. doi:10.1200/JCO.2009.21.8909PubMedGoogle ScholarCrossref
et al. Health-related quality of life outcomes associated with four cisplatin-based doublet chemotherapy regimens for stage IVB recurrent or persistent cervical cancer: a Gynecologic Oncology Group study. Gynecol Oncol
. 2010;119(3):531-537. doi:10.1016/j.ygyno.2010.08.020PubMedGoogle ScholarCrossref
et al. A randomized phase III study comparing three anthracycline-free taxane-based regimens, as first line chemotherapy, in metastatic breast cancer: a Hellenic Cooperative Oncology Group study. Breast Cancer Res Treat
. 2009;115(1):87-99. doi:10.1007/s10549-008-0047-9PubMedGoogle ScholarCrossref
et al. Clinical study of raltitrexed combined with cisplatin for the double-channel chemotherapy in the treatment of patients with advanced colorectal cancer [in Chinese]. Cancer Res Clin
. 2014;26(3):166-168.Google Scholar
et al. Quality of life results from the phase 3 REVEL randomized clinical trial of ramucirumab-plus-docetaxel versus placebo-plus-docetaxel in advanced/metastatic non-small cell lung cancer patients with progression after platinum-based chemotherapy. Lung Cancer
. 2016;93:95-103. doi:10.1016/j.lungcan.2016.01.007PubMedGoogle ScholarCrossref
et al; Gynecologic Oncology Group Study. Randomized phase III trial of cisplatin with or without topotecan in carcinoma of the uterine cervix: a Gynecologic Oncology Group Study. J Clin Oncol
. 2005;23(21):4626-4633. doi:10.1200/JCO.2005.10.021PubMedGoogle ScholarCrossref
III; Gynecologic Oncology Group Study. Quality of life outcomes from a randomized phase III trial of cisplatin with or without topotecan in advanced carcinoma of the cervix: a Gynecologic Oncology Group Study. J Clin Oncol
. 2005;23(21):4617-4625. doi:10.1200/JCO.2005.10.522PubMedGoogle ScholarCrossref
M. Patients at the center: in our practice, and in our use of language. ACP J Club
. 2004;140(1):A11-A12.PubMedGoogle Scholar
J; National Cancer Institute of Canada Clinical Trials Group. Evaluating health-related quality of life in cancer clinical trials: the National Cancer Institute of Canada Clinical Trials Group experience. Value Health
. 2007;10(suppl 2):S138-S145. doi:10.1111/j.1524-4733.2007.00278.xPubMedGoogle ScholarCrossref