Correcting overall survival for the impact of crossover via a rank-preserving structural failure time (RPSFT) model in the RECORD-1 trial of everolimus in metastatic renal-cell carcinoma

Survival analysis from the INCREASE study in PH-ILD: evaluating the impact of treatment crossover on overall mortality

OBJECTIVE

A post-hoc analysis of the INCREASE trial and its open-label extension (OLE) was performed to evaluate whether inhaled treprostinil has a long-term survival benefit in patients with pulmonary hypertension associated with interstitial lung disease (PH-ILD).

METHODS

Two different models of survival were employed; the inverse probability of censoring weighting (IPCW) and the rank-preserving structural failure time (RPSFT) models both allow construction of a pseudo-placebo group, thereby allowing for long-term survival evaluation of patients with PH-ILD receiving inhaled treprostinil. Time-varying stabilised weights were calculated by fitting Cox proportional hazards models based on the baseline and time-varying prognostic factors to generate weighted Cox regression models with associated adjusted HRs.

RESULTS

In the INCREASE trial, there were 10 and 12 deaths in the inhaled treprostinil and placebo arms, respectively, during the 16-week randomised trial. During the OLE, all patients received inhaled treprostinil and there were 29 and 33 deaths in the prior inhaled treprostinil arm and prior placebo arm, respectively. With a conventional analysis, the HR for death was 0.71 (95% CI 0.46 to 1.10; p=0.1227). Both models demonstrated significant reductions in death associated with inhaled treprostinil treatment with HRs of 0.62 (95% CI 0.39 to 0.99; p=0.0483) and 0.26 (95% CI 0.07 to 0.98; p=0.0473) for the IPCW and RPSFT methods, respectively.

CONCLUSION

Two independent modelling techniques that have been employed in the oncology literature both suggest a long-term survival benefit associated with inhaled treprostinil treatment in patients with PH-ILD.

Clinical trial considerations for pediatric cancer drug development

Oncology has been one of the most active therapeutic areas in medicinal products development. Despite this fact, few drugs have been approved for use in pediatric cancer patients when compared to the number approved for adults with cancer. This disparity could be attributed to the fact that many oncology drugs have had orphan drug designation and were exempt from Pediatric Research Equity Act (PREA) requirements. On August 18, 2017, the RACE for Children Act, i.e. Research to Accelerate Cures and Equity Act, was signed into law as Title V of the 2017 FDA Reauthorization Act (FDARA) to amend the PREA. Pediatric investigation is now required if the drug or biological product is intended for the treatment of an adult cancer and directed at a molecular target that FDA determines to be "substantially relevant to the growth or progression of a pediatric cancer." This paper discusses the specific considerations in clinical trial designs and statistical methodologies to be implemented in oncology pediatric clinical programs.

Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.

Adjusting Overall Survival Estimates of Macitentan in Pulmonary Arterial Hypertension After Treatment Switching: Results from the SERAPHIN Study

Introduction

Evaluating overall survival in randomized controlled trials (RCTs) can often be confounded by bias introduced by treatment switching. SERAPHIN was a large RCT that evaluated the effects of long-term treatment with the endothelin receptor antagonist macitentan in patients with pulmonary arterial hypertension. In an intent-to-treat (ITT) analysis, a non-significant decrease in the risk of all-cause mortality up to study closure was reported with macitentan 10 mg versus placebo. As patients could switch treatment when experiencing symptoms of disease progression, this analysis attempts to adjust for the confounding effects on overall survival.

Methods

The inverse probability of censoring weighted (IPCW) and rank-preserving structural failure time (RPSFT) models were used to estimate the treatment effect on overall mortality had there been no treatment switching in SERAPHIN. Time to all-cause death was evaluated up to study closure. Treatment switching was defined as patients in the placebo group switching to open-label macitentan 10 mg, and patients in the macitentan 10 mg group prematurely discontinuing macitentan.

Results

By study closure, 73.2% (183/250) of patients in the placebo group had switched to macitentan 10 mg. Among these patients, exposure time to macitentan 10 mg represented 28.2% of total study treatment exposure (cumulative exposure 134.6 patient-years). At study closure, 24.8% (60/242) of patients in the macitentan 10 mg group were not receiving open-label macitentan; mean time not receiving macitentan was 44.3 weeks. The adjusted hazard ratios (HR) for overall survival using the IPCW and RPSFT methods were lower (HR 0.42, 95% confidence interval [CI] 0.22, 0.81; p = 0.009, and HR 0.33, 95% CI 0.04, 2.83, respectively) than the ITT unadjusted HR (0.80, 95% CI 0.51, 1.24).

Conclusion

These results from the current analyses indicate that in SERAPHIN, the standard ITT analysis was confounded by treatment switching resulting in an underestimation of the benefit of macitentan 10 mg on overall survival. By adjusting for switching, the IPCW and RPSFT models estimated a 58% and 67% reduction in risk of mortality, respectively, with macitentan 10 mg versus placebo.

Trial registration

ClinicalTrials.gov identifier: NCT00660179.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12325-022-02253-8.

A modified weighted log-rank test for confirmatory trials with a high proportion of treatment switching

In confirmatory cancer clinical trials, overall survival (OS) is normally a primary endpoint in the intention-to-treat (ITT) analysis under regulatory standards. After the tumor progresses, it is common that patients allocated to the control group switch to the experimental treatment, or another drug in the same class. Such treatment switching may dilute the relative efficacy of the new drug compared to the control group, leading to lower statistical power. It would be possible to decrease the estimation bias by shortening the follow-up period but this may lead to a loss of information and power. Instead we propose a modified weighted log-rank test (mWLR) that aims at balancing these factors by down-weighting events occurring when many patients have switched treatment. As the weighting should be pre-specified and the impact of treatment switching is unknown, we predict the hazard ratio function and use it to compute the weights of the mWLR. The method may incorporate information from previous trials regarding the potential hazard ratio function over time. We are motivated by the RECORD-1 trial of everolimus against placebo in patients with metastatic renal-cell carcinoma where almost 80% of the patients in the placebo group received everolimus after disease progression. Extensive simulations show that the new test gives considerably higher efficiency than the standard log-rank test in realistic scenarios.

The use of uncertain exposure-A method to define switching and add-on in pharmacoepidemiology

PURPOSE

When defining exposure to pharmacological treatments in pharmacoepidemiology, register data often do not provide information regarding if a pharmacological treatment is a switch or an add-on. This study aims to compare two methods defining switching and add-on therapies and their impact on exposure-outcome associations. Additionally, to guide bias reduction, it aims to describe how the methods relate to immortal time bias and selection bias.

METHODS

Cohort study using Swedish population-based health registers to identify antidepressant (AD) prescriptions as exposures while hospitalizations for psychiatric reasons were used as an empirical outcome example. The first method for exposure definition used conditioning on future exposure (FE), the second used the concept of uncertain exposure (UE). To estimate associations between outcome and exposure categories "Use of one AD," "Use of two or more ADs", and "UE" compared to "Unexposed," hazard ratios (HRs) and 95% confidence intervals were estimated using Cox regression adjusted for age and sex.

RESULTS

Using the UE method, 7.2% of time periods were classified as "UE" with a notable proportion of psychiatric hospitalizations (7.7%) occurring during this time, while when using the FE method these hospitalizations were distributed over unexposed time and AD use time. The FE method resulted in slightly higher associations than the UE method. The highest HR was found during "UE": HR (95% CI) 5.54 (5.06-6.07).

CONCLUSIONS

This study suggests that to reduce the potential immortal time bias, selection bias, and exposure misclassification inherent to the FE method, the UE method could be used for identifying switching and add-on therapies. If not used as a main exposure definition, the UE method may be used to investigate the impact of UE time in a sensitivity analysis.

Assessing the Influence of Subsequent Immunotherapy on Overall Survival in Patients with Unresectable Stage III Non-Small Cell Lung Cancer from the PACIFIC Study

Background

Historically, the standard of care for patients with unresectable, Stage III non-small cell lung cancer had been concurrent chemoradiotherapy. However, outcomes had been poor, with approximately 15% to 32% of patients alive at 5 years. In the placebo-controlled Phase III A PACIFIC trial, consolidation treatment with durvalumab after concurrent chemoradiotherapy significantly improved overall survival (OS) and progression-free survival in patients with unresectable, Stage III non-small cell lung cancer, establishing this regimen as a new standard of care in this setting. In the PACIFIC trial, crossover between treatment arms (durvalumab or placebo) was not permitted. However, after discontinuation from study treatment, patients from both arms of PACIFIC could switch to subsequent anticancer therapy, including durvalumab and other immunotherapies, which is known to influence standard intention-to-treat analysis of OS, potentially underestimating the effect of an experimental drug. Moreover, the introduction of immunotherapies has demonstrated marked improvements in the postprogression, metastatic non-small cell lung cancer setting.

Objective

To examine the influence of subsequent immunotherapy on OS in the PACIFIC trial.

Methods

Both a Rank Preserving Structural Failure Time Model (RPSFTM) and modified 2-stage method were used. RPSFTM assumes that a patient's survival time with no immunotherapy (counterfactual survival time) is equal to the observed time influenced by immunotherapy, multiplied by an acceleration factor, plus the time not influenced. The modified 2-stage method estimates the effect of immunotherapy by comparing postsubsequent-treatment-initiation survival times between patients with and without subsequent immunotherapy. In both models, OS was adjusted to reflect a hypothetical scenario in which no patients received subsequent immunotherapy. RPSFTM was also used for scenarios in which subsequent immunotherapy was received by increasing proportions of placebo patients but none of the durvalumab patients.

Results

In the intention-to-treat analysis (3-year follow-up), durvalumab improved OS versus placebo (stratified hazard ratio = 0.69; 95% CI, 0.55-0.86). Overall, 10% and 27% of durvalumab and placebo patients, respectively, received subsequent immunotherapy. With subsequent immunotherapy removed from both arms, estimated hazard ratio was 0.66 (95% CI, 0.53-0.84) with RPSFTM and 0.68 (95% CI, 0.54-0.85) with the modified 2-stage method. With subsequent immunotherapy removed from the durvalumab arm only (RPSFTM), estimated hazard ratio increased as the proportion of placebo patients receiving subsequent immunotherapy increased, up to 0.75 (95% CI, 0.60-0.94) maximum (assuming all placebo patients with subsequent treatment received immunotherapy).

Conclusions

Results were consistent with the intention-to-treat analysis, supporting the conclusion that durvalumab after chemoradiotherapy provides substantial OS benefit in patients with Stage III, unresectable non-small cell lung cancer. ClinicalTrials.gov identifier: NCT02125461 (Curr Ther Res Clin Exp. 2021; 82:XXX-XXX).

Performance of randomization-based causal methods with and without integrating external data sources for adjusting overall survival in case of extensive treatment switches in placebo-controlled randomized oncology phase 3 trials

In recent placebo-controlled randomized phase 3 oncology trials, evaluation of overall survival with frequent crossover is crucial for regulatory and pricing decisions. The problem is that an intention-to-treat based analysis causes a substantial loss of power to detect causal survival effect without crossover, and performance of existing methods is not satisfactory. In this article, our aims were to evaluate properties of the existing and a proposed Bayesian power prior method where data from an external trial is available. Simulation results suggested that proposed method was the most powerful under typical scenarios where patients with better prognosis are likely to crossover.

Benefit, burden, and impact for a cohort of post-approval cancer combination trials

BACKGROUND

After approval, drug developers often pursue trials aimed at extending the uses of a new drug by combining it with other drugs. Little is known about the risk and benefits associated with such research.

METHODS

To establish a historic benchmark of risk and benefit, we searched Medline and Embase for clinical trials testing anti-cancer drugs in combination within 5 years of approval by the Food and Drug Administration of 12 anti-cancer "index" drugs first licensed 2005-2007 inclusive. Risk was assessed based on grade 3 or above drug-related adverse events; benefit was assessed based on efficacy outcomes and advancement of combinations into clinical practice guidelines or approval by the Food and Drug Administration.

RESULTS

We captured 323 published post-approval trials exploring combinations, including 266 unique combination-indication pairings and enrolling 29,835 patients. The pooled risk ratios for treatment-related grade 3-4 severe adverse events and deaths attributed to the study drugs for trials randomized between a combination arm and a comparator were 1.54 (1.33-1.79) and 1.51 (1.16-1.97), respectively. The pooled hazard ratios for overall survival and progression-free survival were 0.99 (0.92-1.05) and 0.85 (0.79-0.93), respectively. None of the combination-indication pairings launched after initial drug approval received approval by the Food and Drug Administration, and 13 pairings (4.9%) were recommended by the National Comprehensive Cancer Network within 5 years of the first trial within that pairing. The proportion of patients in our sample who participated in trials leading to an approval by the Food and Drug Administration or a National Comprehensive Cancer Network guideline recommendation was 12.7% with 5 years of follow-up, and 22.3% among pairings for which there were 8 years of follow-up.

CONCLUSION

Patients were just as likely to benefit in the treatment arm as the control arm in terms of overall survival, but they were more likely to experience a treatment-related severe adverse event in post-approval trials of combination therapy.

Can contemporary trials of chemotherapy for HER2-negative metastatic breast cancer detect overall survival benefit?

PURPOSE

Although several trials have demonstrated improved progression-free survival (PFS) with first-line regimens for HER2-negative metastatic breast cancer (mBC), overall survival (OS) benefit is elusive. We calculated required sample sizes to power for OS using published data from recent mBC trials.

PATIENTS AND METHODS

Randomized superiority trials of first-line chemotherapy/targeted therapy for HER2-negative mBC including >150 patients, meeting the primary efficacy objective, and published in 2000-2018 were identified. The sample sizes required to power for PFS and OS were calculated retrospectively for each trial using observed results and study/recruitment follow-up durations (α=0.05, two-sided log-rank test, 80% power), and summarized as a factor (x) relative to actual sample size.

RESULTS

Nine of 13 identified trials reported all information required for retrospective sample size calculation. Six had sample sizes larger than required to demonstrate a significant PFS benefit but all would have required larger sample sizes to demonstrate significant OS benefit with the observed results. In ten trials, the required sample size was ≥5-fold larger to power for OS than PFS.

CONCLUSION

Designing trials to test potential new treatments for HER2-negative mBC is challenging, requiring a balance of regulatory acceptability, feasibility, and realistic medical assumptions to calculate sample sizes. Powering for OS is particularly difficult in heterogeneous populations with long postprogression survival, potential crossover, heterogeneous poststudy therapy, and evolving treatment standards. Validated surrogate endpoints are critical. Ongoing trials of cancer immunotherapy (new mode of action) in triple-negative mBC (more homogeneous, shorter OS and postprogression survival, fewer treatment options) may show a new pattern.

Is time to progression associated with post-progression survival in previously treated metastatic non-small cell lung cancer with BRAF V600E mutation? A secondary analysis of phase II clinical trial data

OBJECTIVE

Longer time to progression (TTP) is associated with prolonged post-progression survival (PPS) in anaplastic lymphoma kinase+non-small cell lung cancer (NSCLC). This study evaluated whether TTP is associated with PPS among previously treated patients with metastatic v-Raf murine sarcoma viral oncogene homolog B V600E NSCLC receiving dabrafenib as monotherapy or in combination with trametinib.

DESIGN

Secondary analysis of phase II clinical trial data.

SETTING

Patients who experienced disease progression treated with dabrafenib monotherapy or in combination with trametinib as second line or later in an open-label, non-randomised, phase II study.

PRIMARY OUTCOME MEASURES

The primary outcome was the TTP-PPS association. PPS was assessed with Kaplan-Meier analysis among patients with shorter versus longer TTP (< or ≥6 months). The TTP-PPS association was quantified in the Cox models adjusting for clinical covariates.

RESULTS

Of the 84 included patients who progressed on dabrafenib monotherapy (n=57) or combination therapy (n=27), 60 (71%) died during post-progression follow-up. Patients with TTP ≥6 months experienced significantly longer PPS compared with those with TTP <6 months (median PPS: 9.5 vs 2.7 months, log-rank p<0.001). Each 3 months of longer TTP was associated with a 32% lower hazard of death following progression (HR 0.68, 95% CI 0.52 to 0.88) in the multivariable Cox model. Similar associations were seen in each treatment arm.

CONCLUSION

A longer TTP duration after treatment with dabrafenib monotherapy or combination therapy was associated with significantly longer PPS duration.

TRIAL REGISTRATION NUMBER

NCT01336634; Post-results.

Axitinib, cabozantinib, everolimus, nivolumab, sunitinib and best supportive care in previously treated renal cell carcinoma: a systematic review and economic evaluation

BACKGROUND

Several therapies have recently been approved for use in the NHS for pretreated advanced or metastatic renal cell carcinoma (amRCC), but there is a lack of comparative evidence to guide decisions between them.

OBJECTIVE

To evaluate the clinical effectiveness and cost-effectiveness of axitinib (Inlyta®, Pfizer Inc., NY, USA), cabozantinib (Cabometyx®, Ipsen, Slough, UK), everolimus (Afinitor®, Novartis, Basel, Switzerland), nivolumab (Opdivo®, Bristol-Myers Squibb, NY, USA), sunitinib (Sutent®, Pfizer, Inc., NY, USA) and best supportive care (BSC) for people with amRCC who were previously treated with vascular endothelial growth factor (VEGF)-targeted therapy.

DATA SOURCES

A systematic review and mixed-treatment comparison (MTC) of randomised controlled trials (RCTs) and non-RCTs. Primary outcomes were overall survival (OS) and progression-free survival (PFS). Secondary outcomes were objective response rates (ORRs), adverse events (AEs) and health-related quality of life (HRQoL). MEDLINE, EMBASE and The Cochrane Library were searched from inception to January and June 2016 for RCTs and non-RCTs, respectively. Two reviewers abstracted data and performed critical appraisals.

REVIEW METHODS

A fixed-effects MTC was conducted for OS, PFS [hazard ratios (HRs)] and ORR (odds ratios), and all were presented with 95% credible intervals (CrIs). The RCT data formed the primary analyses, with non-RCTs and studies rated as being at a high risk of bias included in sensitivity analyses (SAs). HRQoL and AE data were summarised narratively. A partitioned survival model with health states for pre progression, post progression and death was developed to perform a cost-utility analysis. Survival curves were fitted to the PFS and OS results from the MTC. A systematic review of HRQoL was undertaken to identify sources of health state utility values.

RESULTS

Four RCTs (n = 2618) and eight non-RCTs (n = 1526) were included. The results show that cabozantinib has longer PFS than everolimus (HR 0.51, 95% CrI 0.41 to 0.63) and both treatments are better than BSC. Both cabozantinib (HR 0.66, 95% CrI 0.53 to 0.82) and nivolumab (HR 0.73, 95% CrI 0.60 to 0.89) have longer OS than everolimus. SAs were consistent with the primary analyses. The economic analysis, using drug list prices, shows that everolimus may be more cost-effective than BSC with an incremental cost-effectiveness ratio (ICER) of £45,000 per quality-adjusted life-year (QALY), as it is likely to be considered an end-of-life treatment. Cabozantinib has an ICER of £126,000 per QALY compared with everolimus and is unlikely to be cost-effective. Nivolumab was dominated by cabozantinib (i.e. more costly and less effective) and axitinib was dominated by everolimus.

LIMITATIONS

Treatment comparisons were limited by the small number of RCTs. However, the key limitation of the analysis is the absence of the drug prices paid by the NHS, which was a limitation that could not be avoided owing to the confidentiality of discounts given to the NHS.

CONCLUSIONS

The RCT evidence suggests that cabozantinib is likely to be the most effective for PFS and OS, closely followed by nivolumab. All treatments appear to delay disease progression and prolong survival compared with BSC, although the results are heterogeneous. The economic analysis shows that at list price everolimus could be recommended as the other drugs are much more expensive with insufficient incremental benefit. The applicability of these findings to the NHS is somewhat limited because existing confidential patient access schemes could not be used in the analysis. Future work using the discounted prices at which these drugs are provided to the NHS would better inform estimates of their relative cost-effectiveness.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016042384.

FUNDING

The National Institute for Health Research Health Technology Assessment programme.

Methods for time-varying exposure related problems in pharmacoepidemiology: An overview

Purpose

Lack of control for time‐varying exposures can lead to substantial bias in estimates of treatment effects. The aim of this study is to provide an overview and guidance on some of the available methodologies used to address problems related to time‐varying exposure and confounding in pharmacoepidemiology and other observational studies. The methods are explored from a conceptual rather than an analytical perspective.

Methods

The methods described in this study have been identified exploring the literature concerning to the time‐varying exposure concept and basing the search on four fundamental pharmacoepidemiological problems, construction of treatment episodes, time‐varying confounders, cumulative exposure and latency, and treatment switching.

Results

A correct treatment episodes construction is fundamental to avoid bias in treatment effect estimates. Several methods exist to address time‐varying covariates, but the complexity of the most advanced approaches—eg, marginal structural models or structural nested failure time models—and the lack of user‐friendly statistical packages have prevented broader adoption of these methods. Consequently, simpler methods are most commonly used, including, for example, methods without any adjustment strategy and models with time‐varying covariates. The magnitude of exposure needs to be considered and properly modelled.

Conclusions

Further research on the application and implementation of the most complex methods is needed. Because different methods can lead to substantial differences in the treatment effect estimates, the application of several methods and comparison of the results is recommended. Treatment episodes estimation and exposure quantification are key parts in the estimation of treatment effects or associations of interest.

Cabozantinib versus everolimus, nivolumab, axitinib, sorafenib and best supportive care: A network meta-analysis of progression-free survival and overall survival in second line treatment of advanced renal cell carcinoma

BACKGROUND

Relative effect of therapies indicated for the treatment of advanced renal cell carcinoma (aRCC) after failure of first line treatment is currently not known. The objective of the present study is to evaluate progression-free survival (PFS) and overall survival (OS) of cabozantinib compared to everolimus, nivolumab, axitinib, sorafenib, and best supportive care (BSC) in aRCC patients who progressed after previous VEGFR tyrosine-kinase inhibitor (TKI) treatment.

METHODOLOGY & FINDINGS

Systematic literature search identified 5 studies for inclusion in this analysis. The assessment of the proportional hazard (PH) assumption between the survival curves for different treatment arms in the identified studies showed that survival curves in two of the studies did not fulfil the PH assumption, making comparisons of constant hazard ratios (HRs) inappropriate. Consequently, a parametric survival network meta-analysis model was implemented with five families of functions being jointly fitted in a Bayesian framework to PFS, then OS, data on all treatments. The comparison relied on data digitized from the Kaplan-Meier curves of published studies, except for cabozantinib and its comparator everolimus where patient level data were available. This analysis applied a Bayesian fixed-effects network meta-analysis model to compare PFS and OS of cabozantinib versus its comparators. The log-normal fixed-effects model displayed the best fit of data for both PFS and OS, and showed that patients on cabozantinib had a higher probability of longer PFS and OS than patients exposed to comparators. The survival advantage of cabozantinib increased over time for OS. For PFS the survival advantage reached its maximum at the end of the first year's treatment and then decreased over time to zero.

CONCLUSION

With all five families of distributions, cabozantinib was superior to all its comparators with a higher probability of longer PFS and OS during the analyzed 3 years, except with the Gompertz model, where nivolumab was preferred after 24 months.

On an enhanced rank-preserving structural failure time model to handle treatment switch, crossover, and dropout

It is very challenging to estimate the comparative treatment effect between a treatment therapy and a control therapy on overall survival in the presence of treatment crossover, switch to an alternative non-study therapy, and non-random patient dropout. Existing methods (e.g., intent-to-treat and per-protocol) are known to be biased. We proposed two new estimators to address these analytical challenges and evaluated their performance via a comprehensive simulation study. The new estimators were constructed by combining an enhanced rank-preserving structural failure time model and the inverse probability censoring weighting approach. In the simulation study, we assessed and compared the performance of the two new estimators with four estimators from existing methods. The simulation results show that the new estimators have much better performance in almost all considered settings compared with the existing estimators. Copyright © 2017 John Wiley & Sons, Ltd.

Association between time to progression and subsequent survival inceritinib-treated patients with advanced ALK-positive non-small-cell lung cancer

OBJECTIVE

Time to progression (TTP) is a surrogate marker of overall survival (OS). However, OS is also dependent on post-progression survival (PPS). This study evaluated the association between TTP and the duration of PPS among adult patients who received ceritinib (Zykadia ¹ ) for the treatment of advanced anaplastic lymphoma kinase positive (ALK+) non-small-cell lung cancer (NSCLC).

RESEARCH DESIGN AND METHODS

A pooled analysis was performed on 181 ASCEND-1 (phase I) and ASCEND-2 (phase II) patients who experienced disease progression while on ceritinib. TTP was assessed on its association with PPS in a Kaplan-Meier analysis and in Cox proportional hazard models, adjusted for clinical covariates.

MAIN OUTCOME MEASURES

Main outcomes measured include TTP, PPS, and OS.

RESULTS

Patients with TTP ≥6 months experienced significantly longer PPS compared to those with TTP <6 months (median: 9.8 vs. 6.5 months, log-rank p-value < .01). When TTP was assessed as a continuous variable, every 3 months of longer TTP was associated with a 21% lower hazard of death following progression (hazard ratio [HR]: 0.79, 95% confidence interval [CI]: 0.63-1.00; adjusted HR: 0.79, 95% CI: 0.64-0.99). This positive association translated into an OS benefit: each 3 months of longer TTP was associated with a lower hazard of death (adjusted HR: 0.46, 95% CI: 0.37-0.58). Median OS was 20.0 months for patients with TTP ≥6 months and was 10.9 months for patients with TTP <6 months.

CONCLUSIONS

A longer duration of TTP after treatment with ceritinib was significantly associated with a longer duration of both PPS and OS.

Everolimus for the Treatment of Advanced Pancreatic Neuroendocrine Tumors: Overall Survival and Circulating Biomarkers From the Randomized, Phase III RADIANT-3 Study

Purpose Everolimus improved median progression-free survival by 6.4 months in patients with advanced pancreatic neuroendocrine tumors (NET) compared with placebo in the RADIANT-3 study. Here, we present the final overall survival (OS) data and data on the impact of biomarkers on OS from the RADIANT-3 study. Methods Patients with advanced, progressive, low- or intermediate-grade pancreatic NET were randomly assigned to everolimus 10 mg/day (n = 207) or placebo (n = 203). Crossover from placebo to open-label everolimus was allowed on disease progression. Ongoing patients were unblinded after final progression-free survival analysis and could transition to open-label everolimus at the investigator's discretion (extension phase). OS analysis was performed using a stratified log-rank test in the intent-to-treat population. The baseline levels of chromogranin A, neuron-specific enolase, and multiple soluble angiogenic biomarkers were determined and their impact on OS was explored. Results Of 410 patients who were enrolled between July 2007 and March 2014, 225 received open-label everolimus, including 172 patients (85%) randomly assigned initially to the placebo arm. Median OS was 44.0 months (95% CI, 35.6 to 51.8 months) for those randomly assigned to everolimus and 37.7 months (95% CI, 29.1 to 45.8 months) for those randomly assigned to placebo (hazard ratio, 0.94; 95% CI, 0.73 to 1.20; P = .30). Elevated baseline chromogranin A, neuron-specific enolase, placental growth factor, and soluble vascular endothelial growth factor receptor 1 levels were poor prognostic factors for OS. The most common adverse events included stomatitis, rash, and diarrhea. Conclusion Everolimus was associated with a median OS of 44 months in patients with advanced, progressive pancreatic NET, the longest OS reported in a phase III study for this population. Everolimus was associated with a survival benefit of 6.3 months, although this finding was not statistically significant. Crossover of patients likely confounded the OS results.

Long-term findings from COMFORT-II, a phase 3 study of ruxolitinib vs best available therapy for myelofibrosis

Ruxolitinib is a Janus kinase (JAK) (JAK1/JAK2) inhibitor that has demonstrated superiority over placebo and best available therapy (BAT) in the Controlled Myelofibrosis Study with Oral JAK Inhibitor Treatment (COMFORT) studies. COMFORT-II was a randomized (2:1), open-label phase 3 study in patients with myelofibrosis; patients randomized to BAT could crossover to ruxolitinib upon protocol-defined disease progression or after the primary end point, confounding long-term comparisons. At week 48, 28% (41/146) of patients randomized to ruxolitinib achieved ⩾35% decrease in spleen volume (primary end point) compared with no patients on BAT (P<0.001). Among the 78 patients (53.4%) in the ruxolitinib arm who achieved ⩾35% reductions in spleen volume at any time, the probability of maintaining response was 0.48 (95% confidence interval (CI), 0.35–0.60) at 5 years (median, 3.2 years). Median overall survival was not reached in the ruxolitinib arm and was 4.1 years in the BAT arm. There was a 33% reduction in risk of death with ruxolitinib compared with BAT by intent-to-treat analysis (hazard ratio (HR)=0.67; 95% CI, 0.44–1.02; P=0.06); the crossover-corrected HR was 0.44 (95% CI, 0.18–1.04; P=0.06). There was no unexpected increased incidence of adverse events with longer exposure. This final analysis showed that spleen volume reductions with ruxolitinib were maintained with continued therapy and may be associated with survival benefits.

A pooled analysis of overall survival in COMFORT-I and COMFORT-II, 2 randomized phase III trials of ruxolitinib for the treatment of myelofibrosis

Ruxolitinib, a potent Janus kinase 1/2 inhibitor, resulted in rapid and durable improvements in splenomegaly and disease-related symptoms in the 2 phase III COMFORT studies. In addition, ruxolitinib was associated with prolonged survival compared with placebo (COMFORT-I) and best available therapy (COMFORT-II). We present a pooled analysis of overall survival in the COMFORT studies using an intent-to-treat analysis and an analysis correcting for crossover in the control arms. Overall, 301 patients received ruxolitinib (COMFORT-I, n=155; COMFORT-II, n=146) and 227 patients received placebo (n=154) or best available therapy (n=73). After a median three years of follow up, intent-to-treat analysis showed that patients who received ruxolitinib had prolonged survival compared with patients who received placebo or best available therapy [hazard ratio=0.65; 95% confidence interval (95%CI): 0.46-0.90; P=0.01]; the crossover-corrected hazard ratio was 0.29 (95%CI: 0.13-0.63). Both patients with intermediate-2- or high-risk disease showed prolonged survival, and patients with high-risk disease in the ruxolitinib group had survival similar to that of patients with intermediate-2-risk disease in the control group. The Kaplan-Meier estimate of overall survival at week 144 was 78% in the ruxolitinib arm, 61% in the intent-to-treat control arm, and 31% in the crossover-adjusted control arm. While larger spleen size at baseline was prognostic for shortened survival, reductions in spleen size with ruxolitinib treatment correlated with longer survival. These findings are consistent with previous reports and support that ruxolitinib offers a survival benefit for patients with myelofibrosis compared with conventional therapies. (clinicaltrials.gov identifiers: COMFORT-I, NCT00952289; COMFORT-II, NCT00934544).

Treatment switching in oncology trials and the acceptability of adjustment methods

Treatment switching has become an important issue in the development and approval of new drugs, particularly in oncology. Randomized controlled trials (RCTs) represent the gold standard for evaluating the effectiveness of interventions, but often patients randomized to the control group are permitted to switch onto the experimental treatment at some point during the trial. This is important, because standard statistical approaches used to analyze RCTs compare groups as randomized, based upon an intention-to-treat principle. When patients in both groups receive the new drug, such analyses do not provide an accurate estimate of the comparative effectiveness of the two treatments. This may lead to inappropriate decision-making - cost-effective drugs may not be approved. Limited healthcare finances may be used inefficiently. Health-related quality-of-life and lives may be lost.

The misguided ethics of crossover trials

Crossover is increasingly favored in trials of cancer therapies; even those that seek to establish the basic efficacy of novel drugs. Crossover is done in part for trial recruitment, but also out of a sense of doing the right thing-offering the investigational agent to more patients. In this paper, we argue that this ethical inclination-that crossover is a preferred trial choice-is misguided. In seeking to sate the desires of participants, we might undermine a trial's ability to answer a meaningful clinical question. When a trial is incapable of answering a question, it becomes unethical. Using a crossover strategy in oncology clinical trials can make trials less ethical, not more.