Impact of disease progression date determination on progression-free survival estimates in advanced lung cancer

Neoadjuvant therapy in non-small cell lung cancer: basis, promise, and challenges

Introduction

Survival rates for early-stage non-small cell lung cancer (NSCLC) remain poor despite the decade-long established standard of surgical resection and systemic adjuvant therapy. Realizing this, researchers are exploring novel therapeutic targets and deploying neoadjuvant therapies to predict and improve clinical and pathological outcomes in lung cancer patients. Neoadjuvant therapy is also increasingly being used to downstage disease to allow for resection with a curative intent. In this review, we aim to summarize the current and developing landscape of using neoadjuvant therapy in the management of NSCLC.

Methods

The PubMed.gov and the ClinicalTrials.gov databases were searched on 15 January 2023, to identify published research studies and trials relevant to this review. One hundred and seven published articles and seventeen ongoing clinical trials were selected, and relevant findings and information was reviewed.

Results & Discussion

Neoadjuvant therapy, proven through clinical trials and meta-analyses, exhibits safety and efficacy comparable to or sometimes surpassing adjuvant therapy. By attacking micro-metastases early and reducing tumor burden, it allows for effective downstaging of disease, allowing for curative surgical resection attempts. Research into neoadjuvant therapy has necessitated the development of surrogate endpoints such as major pathologic response (MPR) and pathologic complete response (pCR) allowing for shorter duration clinical trials. Novel chemotherapy, immunotherapy, and targeted therapy agents are being tested at a furious rate, paving the way for a future of personalized systemic therapy in NSCLC. However, challenges remain that prevent further mainstream adoption of preoperative (Neoadjuvant) therapy. These include the risk of delaying curative surgical resection in scenarios of adverse events or treatment resistance. Also, the predictive value of surrogate markers of disease cure still needs robust verification. Finally, the body of published data is still limited compared to adjuvant therapy. Addressing these concerns with more large scale randomized controlled trials is needed.

The heterogeneity effect of surveillance intervals on progression free survival

Progression-free survival (PFS) is an increasingly important surrogate endpoint in cancer clinical trials. However, the true time of progression is typically unknown if the evaluation of progression status is only scheduled at given surveillance intervals. In addition, comparison between treatment arms under different surveillance schema is not uncommon. Our aim is to explore whether the heterogeneity of the surveillance intervals may interfere with the validity of the conclusion of efficacy based on PFS, and the extent to which the variation would bias the results. We conduct comprehensive simulation studies to explore the aforementioned goals in a two-arm randomized control trial. We introduce three steps to simulate survival data with predefined surveillance intervals under different censoring rate considerations. We report the estimated hazard ratios and examine false positive rate, power and bias under different surveillance intervals, given different baseline median PFS, hazard ratio and censoring rate settings. Results show that larger heterogeneous lengths of surveillance intervals lead to higher false positive rate and overestimate the power, and the effect of the heterogeneous surveillance intervals may depend upon both the life expectancy of the tumor prognoses and the censoring proportion of the survival data. We also demonstrate such heterogeneity effect of surveillance intervals on PFS in a phase III metastatic colorectal cancer trial. In our opinions, adherence to consistent surveillance intervals should be favored in designing the comparative trials. Otherwise, it needs to be appropriately taken into account when analyzing data.

The impact of radiological assessment schedules on progression-free survival in metastatic breast cancer: A systemic review and meta-analysis

BACKGROUND

The impact of interval of restaging on the observed magnitude of benefit of progression-free survival (PFS) is undefined.

MATERIALS AND METHODS

Phase 3 randomized controlled trials (RCTs) investigating anti-neoplastic drugs for metastatic breast cancer which reported the restaging interval and hazard ratio (HR) for PFS were included. Data on study design and study population were collected. HRs and 95% confidence intervals for PFS and OS (overall survival) were pooled in a meta-analysis. Studies were categorized according to short (<9 weeks) or long (≥9 weeks) restaging interval. The differences in PFS and OS effect between trials employing short and long restaging intervals were assessed as subgroup analyses. Analyses were repeated for pre-specified subgroups.

RESULTS

Eighty-nine studies comprising 95 comparisons and 44,901 patients were included. The magnitude of PFS benefit was larger in trials which employed short compared to long restaging intervals, but this difference did not reach the pre-defined threshold for statistical significance (HR = 0.79 vs. 0.86, P = 0.15). Short restaging interval was associated with significantly higher magnitude of effect on PFS in pre-specified subgroups including non-first line trials (HR = 0.78 vs. 0.92, P = 0.04), trials with drugs replacing standard treatment (HR = 0.86 vs. 1.04, P = 0.02) and studies performed in exclusively human epidermal growth factor receptor 2 (HER2) positive disease (HR = 0.72 vs. 0.90, P = 0.02). The magnitude of OS benefit was similar with short and long restaging intervals.

CONCLUSIONS

Shorter restaging intervals are associated with a higher magnitude of effect on PFS, but not OS. Awareness of the impact of the restaging interval on quantification of PFS is important for the design and interpretation of RCTs.

Differential frequency in imaging-based outcome measurement: Bias in real-world oncology comparative-effectiveness studies

Background

Comparative‐effectiveness studies using real‐world data (RWD) can be susceptible to surveillance bias. In solid tumor oncology studies, analyses of endpoints such as progression‐free survival (PFS) are based on progression events detected by imaging assessments. This study aimed to evaluate the potential bias introduced by differential imaging assessment frequency when using electronic health record (EHR)‐derived data to investigate the comparative effectiveness of cancer therapies.

Methods

Using a nationwide de‐identified EHR‐derived database, we first analyzed imaging assessment frequency patterns in patients diagnosed with advanced non‐small cell lung cancer (aNSCLC). We used those RWD inputs to develop a discrete event simulation model of two treatments where disease progression was the outcome and PFS was the endpoint. Using this model, we induced bias with differential imaging assessment timing and quantified its effect on observed versus true treatment effectiveness. We assessed percent bias in the estimated hazard ratio (HR).

Results

The frequency of assessments differed by cancer treatment types. In simulated comparative‐effectiveness studies, PFS HRs estimated using real‐world imaging assessment frequencies differed from the true HR by less than 10% in all scenarios (range: 0.4% to −9.6%). The greatest risk of biased effect estimates was found comparing treatments with widely different imaging frequencies, most exaggerated in disease settings where time to progression is very short.

Conclusions

This study provided evidence that the frequency of imaging assessments to detect disease progression can differ by treatment type in real‐world patients with cancer and may induce some bias in comparative‐effectiveness studies in some situations.

Evaluation of event-free survival as a robust end point in untreated acute myeloid leukemia (Alliance A151614)

Event-free survival (EFS) is controversial as an end point for speeding approvals in newly diagnosed acute myeloid leukemia (AML). We aimed to examine the robustness of EFS, specifically timing of complete remission (CR) in defining induction failure and impact of hematopoietic cell transplantation (HCT). The study included 1884 untreated AML patients enrolled across 5 trials conducted through Alliance for Clinical Trials in Oncology using anthracycline and cytarabine induction chemotherapy. EFS was defined as time from randomization/registration to induction failure, relapse, or death. Three definitions of induction failure were evaluated: failure to achieve CR by 60 days after randomization/registration, failure to achieve CR by the end of all protocol-defined induction courses, and failure to achieve CR by the end of all protocol-defined treatment. We considered either censoring or no censoring at time of non-protocol-mandated HCT. Although relapse and death are firm end points, the determination of induction failure was not consistent across studies. There was minimal impact of censoring at HCT on EFS estimates; however, median EFS estimates differed considerably based on the timing of CR in defining induction failure, with the magnitude of difference being large enough in most cases to lead to incorrect conclusions about efficacy in a single-arm trial, if the trial definition was not consistent with the definition used for the historical control. Timing of CR should be carefully examined in the historical control data used to guide the design of single-arm trials using EFS as the primary end point. Trials were registered at www.clinicaltrials.gov as #NCT00085124, #NCT00416598, # NCT00651261, #NCT01238211, and #NCT01253070.

Neoadjuvant Immunotherapy for NSCLC: Current Concepts and Future Approaches

Lung cancer is the leading cause of cancer-related deaths worldwide. Patients with resectable NSCLC are often treated with surgery and adjuvant chemotherapy. However, these patients continue to have a high risk of recurrence and death. Unfortunately, there has been little progress in the treatment of resectable NSCLC over the past several decades. Neoadjuvant therapy, which has been considered as an approach to improve survival in patients with resectable NSCLC, is a hotly debated topic. A systematic review of 32 randomized trials involving 10,000 patients revealed that there was no difference in survival between preoperative and postoperative chemotherapy. Because of such results and the theoretical concern about resectable tumors progressing on relatively ineffective neoadjuvant chemotherapy, and thus becoming unresectable, neoadjuvant chemotherapy fell out of favor, and many clinicians preferred adjuvant chemotherapy after surgery. However, neoadjuvant therapy has been revived in the past couple of years, with emerging data from various ongoing trials suggesting that neoadjuvant immunotherapy may have significant efficacy and could potentially improve the survival of patients with resectable NSCLC. In this review article, we discuss the evidence supporting the role of neoadjuvant immunotherapy in the multimodal management of resectable NSCLC. We summarize early results of ongoing clinical trials and highlight the challenges in adopting a uniform definition of treatment "success." We address hurdles to be overcome for seeking regulatory approval for neoadjuvant immunotherapy and establishing it as a standard of care. Finally, we provide some perspectives for the future.

Assessment-Schedule Matching in Unanchored Indirect Treatment Comparisons of Progression-Free Survival in Cancer Studies

BACKGROUND

The timing of efficacy-related clinical events recorded at scheduled study visits in clinical trials are interval censored, with the interval duration pre-determined by the study protocol. Events may happen any time during that interval but can only be detected during a planned or unplanned visit. Disease progression in oncology is a notable example where the time to an event is affected by the schedule of visits within a study. This can become a source of bias when studies with varying assessment schedules are used in unanchored comparisons using methods such as matching-adjusted indirect comparisons.

OBJECTIVE

We illustrate assessment-time bias (ATB) in a simulation study based on data from a recent study in second-line treatment for locally advanced or metastatic urothelial carcinoma, and present a method to adjust for differences in assessment schedule when comparing progression-free survival (PFS) against a competing treatment.

METHODS

A multi-state model for death and progression was used to generate simulated death and progression times, from which PFS times were derived. PFS data were also generated for a hypothetical comparator treatment by applying a constant hazard ratio (HR) to the baseline treatment. Simulated PFS times for the two treatments were then aligned to different assessment schedules so that progression events were only observed at set visit times, and the data were analysed to assess the bias and standard error of estimates of HRs between two treatments with and without assessment-schedule matching (ASM).

RESULTS

ATB is highly affected by the rate of the event at the first assessment time; in our examples, the bias ranged from 3 to 11% as the event rate increased. The proposed method relies on individual-level data from a study and attempts to adjust the timing of progression events to the comparator's schedule by shifting them forward or backward without altering the patients' actual follow-up time. The method removed the bias almost completely in all scenarios without affecting the precision of estimates of comparative effectiveness.

CONCLUSIONS

Considering the increasing use of unanchored comparative analyses for novel cancer treatments based on single-arm studies, the proposed method offers a relatively simple means of improving the accuracy of relative benefits of treatments on progression times.

Multitrial Evaluation of Progression-Free Survival as a Surrogate End Point for Overall Survival in First-Line Extensive-Stage Small-Cell Lung Cancer

INTRODUCTION

We previously reported that progression-free survival (PFS) may be a candidate surrogate end point for overall survival (OS) in first-line extensive-stage small-cell lung cancer (ES-SCLC) using data from three randomized trials (Foster, Cancer 2011). In this validation study (N0424-Alliance), we assessed the patient-level and trial-level surrogacy of PFS using data from seven new first-line phase II/III ES-SCLC trials and across all 10 trials as well (seven new, three previous).

METHODS

Individual patient data were utilized across the seven new trials (2259 patients) and all 10 trials (2855 patients). Patient-level surrogacy (Kendall's τ) was assessed using the Clayton copula bivariate survival model. Trial-level surrogacy was assessed through association of the log hazard ratios on OS and PFS across trials, including weighted (by trial size) least squares regression (WLS R²) of Cox model effects and correlation of the copula effects (copula R²). The minimum effect on the surrogate (MES) needed to detect a nonzero treatment effect on OS was also calculated.

RESULTS

The median OS and PFS across all 10 trials were 9.8 and 5.9 months, respectively. PFS showed strong surrogacy within the 7 new trials (copula R² = 0.90 [standard error = 0.27], WLS R² = 0.83 [95% confidence interval: 0.43, 0.95]; MES = 0.67, and Kendall's τ = 0.58) and across all 10 trials (copula R² = 0.81 [standard errors = 0.25], WLS R² = 0.77 [95% confidence interval: 0.47-0.91], MES = 0.70, and Kendall's τ = 0.57).

CONCLUSIONS

PFS demonstrated strong surrogacy for OS in first-line ES-SCLC based on this external validation study of individual patient data. PFS is a good alternative end point to OS and should be considered when resource constraints (time or patient) might make it useful or desirable in place of OS. Additional analyses are needed to assess its appropriateness for targeted agents in this disease setting.

Overview: progression-free survival as an endpoint in clinical trials with solid tumors

Progression-free survival (PFS) is increasingly used as an important and even a primary endpoint in randomized cancer clinical trials in the evaluation of patients with solid tumors for both practical and clinical considerations. Although in its simplest form, PFS is the time from randomization to a predefined endpoint, there are many factors that can influence the exact moment of when disease progression is recorded. In this overview, we review the circumstances that can devalue the use of PFS as a primary endpoint and attempt to provide a pathway for a future desired state when PFS will become not just a secondary alternative to overall survival but rather an endpoint of choice.

The clinical viewpoint: definitions, limitations of RECIST, practical considerations of measurement

In selecting an endpoint in clinical trial design, it is important to consider that the endpoint is both reliably measured and clinically meaningful. As such, overall survival (OS) has traditionally been considered the most clinically relevant and convincing endpoint in clinical trial design as long as it is accompanied by preservation in quality of life. However, progression-free survival (PFS) is increasingly more prominent in clinical trial design because of feasibility issues (smaller sample sizes and shorter follow-up). PFS has the advantage of taking into account not only responsive disease, but stable disease as well, an issue of particular importance in the relapsed and refractory setting in which therapies are often associated with a minimal to nil response but may still confer a survival advantage. Finally, PFS has a significant advantage in molecularly selected populations, in whom OS advantages are difficult to detect due to the effects of crossover. With an understanding of the limitations and biases that are introduced with PFS as a primary endpoint, we believe that PFS is not only a viable but also a necessary alternative to OS in assessing the efficacy of selected novel-targeted therapies in molecularly defined cancer populations. Ultimately, the selection of a clinical trial endpoint should not be based on a one-size-fits all approach; rather, it should be based on the specifics of the therapeutic strategy being tested and the population under study.

Eligibility for bevacizumab as an independent prognostic factor for patients with advanced non-squamous non-small cell lung cancer: a retrospective cohort study

Background

Bevacizumab requires some unique eligibility criteria, such as absence of hemoptysis and major blood vessel invasion by the tumor. The prognostic impact of these bevacizumab-specific criteria has not been evaluated.

Methods

Patients with stage IIIB/IV, non-squamous non-small cell lung cancer who started chemotherapy before the approval of bevacizumab were reviewed. Patients with impaired organ function, poor performance status or untreated/symptomatic brain metastasis were excluded before the evaluation of bevacizumab eligibility. We compared overall survival and time to treatment failure among patients who were eligible (Group A) or ineligible (Group B) to receive bevacizumab.

Results

Among 283 patients with stage IIIB/IV non-squamous non-small cell lung cancer, eligibility for bevacizumab was evaluated in 154 patients. Fifty-seven patients were considered ineligible (Group B) based on one or more of a history of hemoptysis (n = 20), major blood vessel invasion (n = 43) and cardiovascular disease (n = 8). The remaining 97 patients were classified into Group A. Overall survival was significantly better in Group A (median, 14.6 months) than in Group B (median, 7.1 months; p<0.0001). Time to treatment failure was also significantly longer in Group A (median, 6.9 months) than in Group B (median, 3.0 months; p<0.0001). Adjusted hazard ratios of bevacizumab eligibility for overall survival and time to treatment failure were 0.48 and 0.38 (95% confidence intervals, 0.33–0.70 and 0.25–0.58), respectively.

Conclusion

Eligibility for bevacizumab itself represents a powerful prognostic factor for patients with non-squamous non-small cell lung cancer. The proportion of patients who underwent first-line chemotherapy without disease progression or unacceptable toxicity can also be biased by bevacizumab eligibility. Selection bias can be large in clinical trials of bevacizumab, so findings from such trials should be interpreted with extreme caution.