Development and Evaluation of a Method to Correct Misinterpretation of Clinical Trial Results With Long-term Survival

Flexible quantitative bias analysis for unmeasured confounding in subject-level indirect treatment comparisons with proportional hazards violation

BACKGROUND

Indirect treatment comparisons can provide evidence of relative efficacy for novel therapies when implementation of a randomised controlled trial is infeasible. However, such comparisons are vulnerable to unmeasured confounding bias due to incomplete data collection and non-random treatment assignment. Quantitative bias analysis (QBA) is a framework used to assess the sensitivity of a study's conclusions to unmeasured confounding. As indirect comparisons between therapies with differing treatment modalities may result in violation of the proportional hazards (PH) assumption, QBA methods that are applicable in this context are required. However, few QBA methods are valid under PH violation.

METHODS

We proposed a simulation-based QBA framework which quantifies the sensitivity of the difference in restricted mean survival time (dRMST) to unmeasured confounding, and is therefore valid under violation of the PH assumption. The proposed framework utilises Bayesian data augmentation for the multiple imputation of an unmeasured confounder with user-specified characteristics. Adjustment of dRMST is then implemented in a weighted analysis using the imputed values. The accuracy and precision of our proposed imputation-based adjustment method was assessed through a simulation study. Confounded data was simulated using a common non-PH data generating process, and imputation-based effect estimates were compared against estimates obtained following adjustment for all confounders. Implementation of the proposed QBA framework was also illustrated using a data from an external control arm study demonstrating clear PH violation.

RESULTS

Imputation-based adjustment using Bayesian data augmentation was observed to estimate the true adjusted dRMST with minimal bias. Moreover, the bias was comparable to that observed under adjustment when all confounders were measured. Application of the proposed QBA framework to an indirect treatment comparison study enabled identification of the characteristics of an unmeasured confounder that would be required to nullify the study's conclusions.

CONCLUSIONS

Imputation-based adjustment can accurately recover the true adjusted dRMST in the presence of unmeasured confounding with known exposure and outcome associations. Therefore, the proposed QBA framework can correctly determine the characteristics required by an unmeasured confounder to invalidate a study's conclusions. Consequently, this framework enables the construction of sensitivity analyses to investigate the robustness of relative efficacy evidence derived from indirect treatment comparisons which exhibit PH violation.

Estimand-based inference in the presence of long-term survivors

In this article, we develop nonparametric inference methods for comparing survival data across two samples, beneficial for clinical trials of novel cancer therapies where long-term survival is critical. These therapies, including immunotherapies and other advanced treatments, aim to establish durable effects. They often exhibit distinct survival patterns such as crossing or delayed separation and potentially leveling-off at the tails of survival curves, violating the proportional hazards assumption and rendering the hazard ratio inappropriate for measuring treatment effects. Our methodology uses the mixture cure framework to separately analyze cure rates of long-term survivors and the survival functions of susceptible individuals. We evaluated a nonparametric estimator for the susceptible survival function in a one-sample setting. Under sufficient follow-up, it is expressed as a location-scale-shift variant of the Kaplan-Meier estimator. It retains desirable features of the Kaplan-Meier estimator, including inverse-probability-censoring weighting, product-limit estimation, self-consistency, and nonparametric efficiency. Under insufficient follow-up, it can be adapted by incorporating a suitable cure rate estimator. In the two-sample setting, in addition to using the difference in cure rates to measure long-term effects, we propose a graphical estimand to compare relative treatment effects on susceptible subgroups. This process, inspired by Kendall's tau, compares the order of survival times among susceptible individuals. Large-sample properties of the proposed methods are derived for inference and their finite-sample properties are evaluated through simulations. The methodology is applied to analyze digitized data from the CheckMate 067 trial.

Immune Checkpoint Inhibitors Affect Post-Progression Survival of Specific Patient Subgroups With Advanced Hepatocellular Carcinoma: A Study Cohorts' Analysis

OBJECTIVES

Immunotherapy-based regimens (IMBs), compared with tyrosine-kinase inhibitors (TKIs), improve the overall survival (OS) of patients with advanced hepatocellular carcinoma (aHCC). The aim of the study was to explore the interaction of prognostic factors with survival in study cohorts receiving IMB or TKI.

METHODS

A systematic search was performed and single arms of phase III trials including IMB or TKI were selected. Analysis of IMB and TKI cohorts was performed, and the relationship between progression-free survival (PFS) with OS was assessed. Finally, 13 variables were extracted, and their relationships with survival in the two groups were evaluated.

RESULTS

Thirty-three study cohorts were selected. Longer OS and post-progression survival (PPS) were evident in the group of IMB, while the relationship of PFS with OS was significant only in the TKI cohorts (β = 0.527, p = 0.007). Prognostic factors in the IMB cohorts did not report any significant relationship with OS, while among patients receiving TKIs, longer OS was documented with elder age (β = 0.577, p = 0.003) and good performance status (β = 0.500, p = 0.011). Conversely, in the IMB cohorts, PPS increased with hepatitis B virus (HBV) (β = 0.756, p = 0.030) and Barcelona Clinic Liver Classification (BCLC) stage (β = 0.898, p = 0.002).

CONCLUSION

In contrast to TKIs, IMBs improved the outcome of patients with aHCC by increasing PPS, particularly in patients with BCLC stage C and HBV-related hepatopathy, but the outcome improvement was lost in patients with hepatitis C virus-related liver disease.

[A simulation study of the reliability and accuracy of Cox-TEL method for estimating hazard ratio and difference in proportions for long-term survival data containing cured patients]

OBJECTIVE

To explore the applicable conditions of the Cox-TEL (Cox PH-Taylor expansion adjustment for long-term survival data) method for analysis of survival data that contain cured patients.

METHODS

The simulated survival data method based on Weibull distribution was used to simulate and generate the survival data with different cure rates, censored rates, and cure rate differences. The Cox-TEL method was used for analysis of the generated simulation data, and its performance was evaluated by calculating its type Ⅰ error and power.

RESULTS

Almost all the type Ⅰ error of the hazard ratios (HRs) obtained by the Cox-TEL method under different conditions were slightly greater than 0.05, and this method showed a good test power for estimating the HRs for data with a large sample size and a large difference in proportions (DPs). For the data of cured patients, the type Ⅰ error of the DPs obtained by the Cox-TEL method was well around 0.05, and its test power was robust in most of the scenarios.

CONCLUSION

The Cox-TEL method is effective for analyzing data of uncured patients and obtaining reliable HRs for most of the survival data with a sample size, a low censored rates, and a large difference in cure rates. The method is capable of accurately estimating the DPs regardless of the sample size, censored rates, or the cure rates.

Efficacy and Safety of Anti-Programmed Cell Death Protein 1/Programmed Death-Ligand 1 Antibodies Plus Chemotherapy as First-Line Treatment for NSCLC in the People's Republic of China: a Systematic Review and Meta-Analysis

Introduction

The available approved anticancer drugs for Chinese patients are relatively limited because of China's low participation rate in international clinical trials. Therefore, a focus on approved anti-programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) drugs in China is needed. This study aims to assess the heterogeneity of anti-PD-1/PD-L1 antibodies manufactured in China (domestic PD-1/PD-L1) and overseas (imported PD-1/PD-L1) when combined with chemotherapy as the first-line treatment of NSCLC.

Methods

A systematic search was performed using PubMed, EMBASE, and Cochrane Library of publications up to July 13, 2023. Meta-analysis was applied to compare the efficacy and safety profile between anti-PD-1/PD-L1 antibodies plus chemotherapy (PD-1/PD-L1+Chemo) and chemotherapy alone using STATA software. Pooled hazard ratios for progression-free survival and overall survival, odds ratios for objective response rate, and incidence rate of grade greater than or equal to three treatment-related adverse events with 95% confidence intervals were calculated in the domestic group and imported group by a random-effects model, and the heterogeneity between the two estimates was assessed.

Results

There were 14 eligible clinical studies with a total of 3951 patients involved in this analysis, including eight studies of domestic PD-1/PD-L1+Chemo and six studies of imported PD-1/PD-L1+Chemo. The study revealed that there was no significant difference between domestic and imported PD-1/PD-L1+Chemo in overall survival (p = 0.80), progression-free survival (p = 0.53), and incidence rate of grade greater than or equal to three treatment-related adverse events (p = 0.10). Nevertheless, the objective response rate of imported PD-1/PD-L1+Chemo was significantly higher than that of domestic PD-1/PD-L1+Chemo (p = 0.03).

Conclusions

Domestic anti-PD-1/PD-L1 antibodies plus chemotherapy were found to have comparable efficacy and safety to those combined with imported anti-PD-1/PD-L1 antibodies based on current evidence.

Individualized survival prediction and surgery recommendation for patients with glioblastoma

Background

There is a lack of individualized evidence on surgical choices for glioblastoma (GBM) patients.

Aim

This study aimed to make individualized treatment recommendations for patients with GBM and to determine the importance of demographic and tumor characteristic variables in the selection of extent of resection.

Methods

We proposed Balanced Decision Ensembles (BDE) to make survival predictions and individualized treatment recommendations. We developed several DL models to counterfactually predict the individual treatment effect (ITE) of patients with GBM. We divided the patients into the recommended (Rec.) and anti-recommended groups based on whether their actual treatment was consistent with the model recommendation.

Results

The BDE achieved the best recommendation effects (difference in restricted mean survival time (dRMST): 5.90; 95% confidence interval (CI), 4.40-7.39; hazard ratio (HR): 0.71; 95% CI, 0.65-0.77), followed by BITES and DeepSurv. Inverse probability treatment weighting (IPTW)-adjusted HR, IPTW-adjusted OR, natural direct effect, and control direct effect demonstrated better survival outcomes of the Rec. group.

Conclusion

The ITE calculation method is crucial, as it may result in better or worse recommendations. Furthermore, the significant protective effects of machine recommendations on survival time and mortality indicate the superiority of the model for application in patients with GBM. Overall, the model identifies patients with tumors located in the right and left frontal and middle temporal lobes, as well as those with larger tumor sizes, as optimal candidates for SpTR.

Two-phase designs with failure time processes subject to nonsusceptibility

Epidemiological studies based on 2-phase designs help ensure efficient use of limited resources in situations where certain covariates are prohibitively expensive to measure for a full cohort. Typically, these designs involve 2 steps: In phase I, data on an outcome and inexpensive covariates are acquired, and in phase II, a subsample is chosen in which the costly variable of interest is measured. For right-censored data, 2-phase designs have been primarily based on the Cox model. We develop efficient 2-phase design strategies for settings involving a fraction of long-term survivors due to nonsusceptibility. Using mixture models accommodating a nonsusceptible fraction, we consider 3 regression frameworks, including (a) a logistic "cure" model, (b) a proportional hazards model for those who are susceptible, and (c) regression models for susceptibility and failure time in those susceptible. Importantly, we introduce a novel class of bivariate residual-dependent designs to address the unique challenges presented in scenario (c), which involves 2 parameters of interest. Extensive simulation studies demonstrate the superiority of our approach over various phase II subsampling schemes. We illustrate the method through applications to the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial.

Cox Proportional Hazard Ratios Overestimate Survival Benefit of Immune Checkpoint Inhibitors: Cox-TEL Adjustment and Meta-Analyses of Programmed Death-Ligand 1 Expression and Immune Checkpoint Inhibitor Survival Benefit

INTRODUCTION

Survival benefit of immune checkpoint inhibitor (ICI) therapy in lung cancer is not fully understood.

METHODS

PubMed-cataloged publications through February 14, 2022, were queried for randomized controlled trials of ICI in lung cancer, and identified publications were reviewed for inclusion. Reported Cox hazard ratios (HRs) for overall survival were transformed to Cox-TEL HR for ICI short-term survivors (ST-HR) and difference in proportions for patients with long-term survival (LT-DP). Meta-analyses were performed using a frequentist random-effect model. Outcomes of interest were pooled overall survival Cox HR, ST-HR, and LT-DP in NSCLC, stratified by programmed death-ligand 1 (PD-L1) level (primary outcome) and ICI treatment line (secondary).

RESULTS

A total of nine publications representing eight clinical trials were selected for meta-analysis. Primary analysis yielded the following metrics for patients with PD-L1 expression less than 1%, more than or equal to 1%, and more than or equal to 50%, respectively: pooled Cox HR, 0.71 (95% confidence interval [CI]: 0.62-0.82), 0.74 (95% CI: 0.68-0.82), and 0.62 (95% CI: 0.54-0.70); pooled ST-HR, 0.91 (95% CI: 0.79-1.05), 0.88 (95% CI: 0.82-0.94), and 0.70 (95% CI: 0.60-0.83); and pooled LT-DP, 0.10 (95% CI: 0.00-0.20), 0.09 (95% CI: 0.06-0.12), and 0.11 (95% CI: 0.05-0.17). Results of secondary analysis revealed LT-DP of approximately 10% across treatment lines.

CONCLUSIONS

This study reveals an approximately 10% long-term survival probability increment in ICI long-term survivors across PD-L1-positive subpopulations in both ICI treatment lines. Furthermore, ST-HR was consistently poorer than Cox HR. For patients with PD-L1 less than 1%, neither LT-DP nor ST-HR achieved statistical significance. The analysis provides greater insight into the treatment effect of ICI in published trials.

Immune checkpoint inhibitors as first line in advanced melanoma: Evaluating progression-free survival based on reconstructed individual patient data

BACKGROUND

In patients with advanced melanoma, immune-checkpoint inhibitors (ICIs) represent the mainstay for first line treatment. Recently, relatlimab+nivolumab was proposed as a new combination therapy. This review was aimed at summarizing the current data of effectiveness for ICIs. Progression-free survival (PFS) was the endpoint of our analysis.

METHODS

After a standard literature search, Phase II/III studies comparing different ICI regimens in previously untreated advanced melanoma patients were analyzed. Patient-level data were reconstructed from Kaplan-Meier curves by application of the IPDfromKM method. These reconstructed datasets were used to perform indirect comparisons between treatments. Standard statistical testing was used, including hazard ratio and medians. A secondary analysis employed the restricted mean survival time.

RESULTS

Six trials were included in our analysis. Information on PFS from these trials was pooled according to the following treatments: nivolumab or pembrolizumab as monotherapy, or in combination with ipilimumab, and relatlimab + nivolumab. Pembrolizumab+ipilimumab showed significantly better PFS compared with the other treatments; nivolumab+ipilimumab ranked second; the other treatments showed a similar survival pattern.

CONCLUSIONS

The picture of comparative effectiveness resulting from our analysis is complex. The IPDfromKM method is advantageous because it accounts for the length of follow-up but loses the balance between treatment group and controls determined by randomization. Based on indirect comparisons, the combination of pembrolizumab+ipilimumab showed a particularly high efficacy, and so deserves further investigation. While the effect of between-trial differences in inclusion criteria plays an important role, our results do not support the proposal of relatlimab+nivolumab as a new standard of care.

Analysis of Cancer Survival Associated With Immune Checkpoint Inhibitors After Statistical Adjustment: A Systematic Review and Meta-analyses

IMPORTANCE

Appropriate clinical decision-making relies on accurate data interpretation, which in turn relies on the use of suitable statistical models. Long tails and early crossover-2 features commonly observed in immune checkpoint inhibitor (ICI) survival curves-raise questions as to the suitability of Cox proportional hazards regression for ICI survival analysis. Cox proportional hazards-Taylor expansion adjustment for long-term survival data (Cox-TEL) adjustment may provide possible solutions in this setting.

OBJECTIVE

To estimate overall survival and progression-free survival benefits of ICI therapy vs chemotherapy using Cox-TEL adjustment.

DATA SOURCES

A PubMed search was performed for all cataloged publications through May 22, 2022.

STUDY SELECTION

The search was restricted to randomized clinical trials with search terms for ICIs and lung cancer, melanoma, or urothelial carcinoma. The publications identified were further reviewed for inclusion.

DATA EXTRACTION AND SYNTHESIS

Cox proportional hazards ratios (HRs) were transformed to Cox-TEL HRs for patients with short-term treatment response (ie, short-term survivor) (ST-HR) and difference in proportions for patients with long-term survival (LT-DP) by Cox-TEL. Meta-analyses were performed using a frequentist random-effects model.

MAIN OUTCOMES AND MEASURES

Outcomes of interest were pooled overall survival (primary outcome) and progression-free survival (secondary outcome) HRs, ST-HRs, and LT-DPs. Subgroup analyses stratified by cancer type also were performed.

RESULTS

A total of 1036 publications was identified. After 3 levels of review against inclusion criteria, 13 clinical trials (7 in non-small cell lung cancer, 3 in melanoma, and 3 in urothelial carcinoma) were selected for the meta-analysis. In the primary analysis, pooled findings were 0.75 (95% CI, 0.70-0.81) for HR, 0.86 (95% CI, 0.81-0.92) for ST-HR, and 0.08 (95% CI, 0.06-0.10) for LT-DP. In the secondary analysis, the pooled values for progression-free survival were 0.77 (95% CI, 0.64-0.91) for HR, 1.02 (95% CI, 0.84-1.24) for ST-HR, and 0.10 (95% CI, 0.06-0.14) for LT-DP.

CONCLUSIONS AND RELEVANCE

This systematic review and meta-analysis of ICI clinical trial results noted consistently larger ST-HRs vs Cox HRs for ICI therapy, with an LT-DP of approximately 10%. These results suggest that Cox HRs may not provide a full picture of survival outcomes when the risk reduction from treatment is not constant, which may aid in the decision-making process of oncologists and patients.

Preoperative and Postoperative Systemic Therapy for Operable Non-Small-Cell Lung Cancer

Cisplatin-based adjuvant chemotherapy remains the standard of care for patients with resected stage II or III non-small-cell lung cancer. However, biomarker-informed clinical trials are starting to push the management of early-stage lung cancer beyond cytotoxic chemotherapy. This review explores recent and ongoing studies focused on improving cytotoxic chemotherapy and incorporating targeted and immunotherapies in the management of early-stage, resectable lung cancer. Adjuvant osimertinib for patients with EGFR-mutant tumors, preoperative chemoimmunotherapy, and adjuvant immunotherapy could improve outcomes for selected patients with resectable lung cancer, and ongoing or planned studies leveraging biomarkers, immunotherapy, and targeted therapy may further improve survival. We also discuss the unique barriers associated with clinical trials of early-stage lung cancer and the need for innovative trial designs to overcome these challenges.