Challenges of modelling approaches for network meta-analysis of time-to-event outcomes in the presence of non-proportional hazards to aid decision making: Application to a melanoma network

Bayesian pairwise meta-analysis of time-to-event outcomes in the presence of non-proportional hazards: A simulation study of flexible parametric, piecewise exponential and fractional polynomial models

BACKGROUND

Traditionally, meta-analysis of time-to-event outcomes reports a single pooled hazard ratio assuming proportional hazards (PH). For health technology assessment evaluations, hazard ratios are frequently extrapolated across a lifetime horizon. However, when treatment effects vary over time, an assumption of PH is not always valid. The Royston-Parmar (RP), piecewise exponential (PE), and fractional polynomial (FP) models can accommodate non-PH and provide plausible extrapolations of survival curves beyond observed data.

METHODS

Simulation study to assess and compare the performance of RP, PE, and FP models in a Bayesian framework estimating restricted mean survival time difference (RMSTD) at 50 years from a pairwise meta-analysis with evidence of non-PH. Individual patient data were generated from a mixture Weibull distribution. Twelve scenarios were considered varying the amount of follow-up data, number of trials in a meta-analysis, non-PH interaction coefficient, and prior distributions. Performance was assessed through bias and mean squared error. Models were applied to a metastatic breast cancer example.

RESULTS

FP models performed best when the non-PH interaction coefficient was 0.2. RP models performed best in scenarios with complete follow-up data. PE models performed well on average across all scenarios. In the metastatic breast cancer example, RMSTD at 50-years ranged from -14.6 to 8.48 months.

CONCLUSIONS

Synthesis of time-to-event outcomes and estimation of RMSTD in the presence of non-PH can be challenging and computationally intensive. Different approaches make different assumptions regarding extrapolation and sensitivity analyses varying key assumptions are essential to check the robustness of conclusions to different assumptions for the underlying survival function.

Identifying optimal ALK inhibitors in first- and second-line treatment of patients with advanced ALK-positive non-small-cell lung cancer: a systematic review and network meta-analysis

OBJECTIVES

To compare the efficacy, safety and effects on quality of life of different ALK-inhibitors for global and Asian patients with advanced ALK-positive non-small-cell lung cancer (NSCLC).

METHODS

The included RCTs were identified through a systematic search of PubMed, EMBASE, Cochrane Library, Clinical Trials.gov, and major cancer conferences. The assessment of progression-free survival (PFS), intracranial PFS, overall survival (OS), and patient-reported outcomes (PROs) was carried out using restricted mean survival time (RMST) model, fractional polynomial model and Royston-Parmar model. Time-invariant hazard ratio (HR) models were also used to validate and supplement the primary analysis. Objective response rate (ORR) and adverse events with any grade, grade 3-5 were assessed through a Bayesian network meta-analysis. The primary measures for OS, PFS, and PROs were HR and RMST. The odds ratio was the metric for evaluating safety, ORR, 12-month PFS rate, 24-month OS rate, and the 12-month non-deterioration rate of PROs. Subgroup analyses based on patient characteristics were performed.

RESULTS

A total of fourteen studies (ten for first-line, four for second-line) consisting of nine treatments (chemotherapy, crizotinib, alectinib [600mg BID], low-dose alectinib [300mg BID], brigatinib, ceritinib, ensartinib, envonalkib, and lorlatinib) were included. In the first-line setting, alectinib showed a significant advantage over crizotinib and had the longest OS among all ALK-inhibitors. Compared to crizotinib, lorlatinib had the best efficacy regarding PFS for global patients, followed closely by alectinib and brigatinib. For Asian patients, alectinib significantly improved PFS compared to other treatments. In second-line, alectinib had the highest PFS for patients pretreated with crizotinib, followed by brigatinib, ceritinib and chemotherapy. Alectinib, irrespective of the dose, was the safest first-line option, whereas lorlatinib, brigatinib, and ceritinib showed poorer safety profiles. Alectinib was also the safest ALK-inhibitor for crizotinib-resistant patients. Brigatinib had the best performance in terms of PROs.

CONCLUSIONS

Considering both efficacy and safety, alectinib appears to be the preferable treatment in first-line and second-line, particularly for Asian patients.

Twenty years of network meta-analysis: Continuing controversies and recent developments

Network meta-analysis (NMA) is an extension of pairwise meta-analysis (PMA) which combines evidence from trials on multiple treatments in connected networks. NMA delivers internally consistent estimates of relative treatment efficacy, needed for rational decision making. Over its first 20 years NMA's use has grown exponentially, with applications in both health technology assessment (HTA), primarily re-imbursement decisions and clinical guideline development, and clinical research publications. This has been a period of transition in meta-analysis, first from its roots in educational and social psychology, where large heterogeneous datasets could be explored to find effect modifiers, to smaller pairwise meta-analyses in clinical medicine on average with less than six studies. This has been followed by narrowly-focused estimation of the effects of specific treatments at specific doses in specific populations in sparse networks, where direct comparisons are unavailable or informed by only one or two studies. NMA is a powerful and well-established technique but, in spite of the exponential increase in applications, doubts about the reliability and validity of NMA persist. Here we outline the continuing controversies, and review some recent developments. We suggest that heterogeneity should be minimized, as it poses a threat to the reliability of NMA which has not been fully appreciated, perhaps because it has not been seen as a problem in PMA. More research is needed on the extent of heterogeneity and inconsistency in datasets used for decision making, on formal methods for making recommendations based on NMA, and on the further development of multi-level network meta-regression.

A network meta-analysis of efficacy and safety for first-line and second/further-line therapies in postmenopausal women with hormone receptor-positive, HER2-negative, advanced breast cancer

BACKGROUND

Hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR + /HER2 -) advanced breast cancer is a prevalent subtype among postmenopausal women. Despite the growing number of randomized clinical trials (RCTs) exploring this topic, the efficacy and safety of first-line and second/further-line treatments remain uncertain. Accordingly, our aim was to conduct a comprehensive evaluation of the efficacy and safety of these therapies through network meta-analysis.

METHODS

RCTs were identified by searching Pubmed, Embase, and major cancer conferences. The efficacy of interventions was assessed using the hazard ratios (HRs) of progression-free survival (PFS) and overall survival (OS), while safety was indicated by the incidence of any grade adverse events (AEs), grade 3-5 AEs, AEs leading to treatment discontinuation, and AEs leading to death. Both time-variant HRs fractional polynomial models and time-invariant HRs Cox-proportional hazards models were considered for handling time-to-event data. Safety indicators were analyzed using Bayesian network meta-analysis. Additionally, subgroup analyses were conducted based on patient characteristics.

RESULTS

A total of 41 RCTs (first-line 17, second/further-lines 27) were included in the analysis. For first-line treatment, the addition of Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors to endocrine therapy significantly improved therapeutic efficacy in terms of both PFS and OS, demonstrating the best performance across all mechanisms. Specifically, the combination of Abemaciclib and Letrozole demonstrated the most favorable performance in terms of PFS, while Ribociclib plus Fulvestrant yielded the best outcomes in OS. Incorporating the immune checkpoint inhibitor Avelumab into the regimen with CDK4/6 inhibitors and selective estrogen receptor degraders significantly enhanced both PFS and OS in second-line or later treatments. Regarding safety, endocrine monotherapy performed well. Regarding safety, endocrine monotherapy performed well. There is mounting evidence suggesting that most CDK4/6 inhibitors may demonstrate poorer performance with respect to hematologic AEs. However, additional evidence is required to further substantiate these findings.

CONCLUSIONS

CDK4/6 inhibitors, combined with endocrine therapy, are pivotal in first-line treatment due to their superior efficacy and manageable AEs. For second/further-line treatment, adding immune checkpoint inhibitors to CDK4/6 inhibitors plus endocrine therapy may produce promising results. However, to reduce the results' uncertainty, further trials comparing these novel treatments are warranted.

TRIAL REGISTRATION

Registration number: PROSPERO (CRD42022377431).

Challenges in conducting fractional polynomial and standard parametric network meta-analyses of immune checkpoint inhibitors for first-line advanced renal cell carcinoma

Aim: Network meta-analyses (NMAs) increasingly feature time-varying hazards to account for non-proportional hazards between different drug classes. This paper outlines an algorithm for selecting clinically plausible fractional polynomial NMA models. Methods: The NMA of four immune checkpoint inhibitors (ICIs) + tyrosine kinase inhibitors (TKIs) and one TKI therapy for renal cell carcinoma (RCC) served as case study. Overall survival (OS) and progression free survival (PFS) data were reconstructed from the literature, 46 models were fitted. The algorithm entailed a-priori face validity criteria for survival and hazards, based on clinical expert input, and predictive accuracy against trial data. Selected models were compared with statistically best-fitting models. Results: Three valid PFS and two OS models were identified. All models overestimated PFS, the OS model featured crossing ICI + TKI versus TKI curves as per expert opinion. Conventionally selected models showed implausible survival. Conclusion: The selection algorithm considering face validity, predictive accuracy, and expert opinion improved the clinical plausibility of first-line RCC survival models.

A Comparison of Alternative Network Meta-Analysis Methods in the Presence of Nonproportional Hazards: A Case Study in First-Line Advanced or Metastatic Renal Cell Carcinoma

OBJECTIVES

Network meta-analysis (NMA) of time-to-event outcomes based on constant hazard ratios can result in biased findings when the proportional hazards (PHs) assumption does not hold in a subset of trials. We aimed to summarize the published non-PH NMA methods for time-to-event outcomes, demonstrate their application, and compare their results.

METHODS

The following non-PH NMA methods were compared through an illustrative case study in oncology of 4 randomized controlled trials in terms of progression-free survival and overall survival: (1) 1-step or (2) 2-step multivariate NMAs based on traditional survival distributions or fractional polynomials, (3) NMAs with restricted cubic splines for baseline hazard, and (4) restricted mean survival NMA.

RESULTS

For progression-free survival, the PH assumption did not hold across trials and non-PH NMA methods better reflected the relative treatment effects over time. The most flexible models (fractional polynomials and restricted cubic splines) fit better to the data than the other approaches. Estimated hazard ratios obtained with different non-PH NMA methods were similar at 5 years of follow-up but differed thereafter in the extrapolations. Although there was no strong evidence of PH violation for overall survival, non-PH NMA methods captured this uncertainty in the relative treatment effects over time.

CONCLUSIONS

When the PH assumption is questionable in a subset of the randomized controlled trials, we recommend assessing alternative non-PH NMA methods to estimate relative treatment effects for time-to-event outcomes. We propose a transparent and explicit stepwise model selection process considering model fit, external constraints, and clinical validity. Given inherent uncertainty, sensitivity analyses are suggested.

A systematic review and network meta-analysis of first-line immune checkpoint inhibitor combination therapies in patients with advanced non-squamous non-small cell lung cancer

INTRODUCTION

Clinical evidence suggests that first-line immune checkpoint inhibitor (ICI) combination therapies can improve survival in patients with advanced non-squamous non-small cell lung cancer (nsq-NSCLC). However, the optimal strategy remains unknown without a systematic comparison of their long-term effects.

METHODS

We performed a systematic review and network meta-analysis by retrieving up-to-date literature from PubMed® (National Library of Medicine, Bethesda, MD, USA), Embase® (Elsevier, Amsterdam, Netherlands), MEDLINE® (National Library of Medicine), ClinicalTrials.gov (National Library of Medicine), and major international conference publications. Published studies and abstracts comparing first-line ICI combination therapies with other treatments for patients with advanced nsq-NSCLC were included. Restricted mean survival time (RMST) was measured over 12 months for progression-free survival (PFS) and 18 months for overall survival (OS), and the Royston-Parmar model was used to extrapolate and compare data for the long-term outcomes.

RESULTS

We included a total of 11 trials involving 12 therapies and 6,130 patients. Pembrolizumab plus chemotherapy exhibited the best overall survival (OS) benefit at both 18 and 60 months [RMST = 2.95, 95% confidence interval (CI) 1.96 to 3.97; life-years gained over a 5-year period = 2.18 years]. Nivolumab plus bevacizumab plus chemotherapy was found to present the best progression-free survival (PFS) benefit at 12 months (RMST 3.02, 95% CI 2.11 to 3.91), whereas atezolizumab plus bevacizumab plus chemotherapy showed the best PFS benefit at 36 months (life-years gained over 3 years = 1.22 years). Subgroup analyses showed that among patients with programmed death-ligand 1 (PD-L1) expression ≥ 50%, atezolizumab plus chemotherapy and nivolumab plus ipilimumab resulted in superior OS benefits at 18 and 60 months, respectively. Among patients with PD-L1 expression< 1%, pembrolizumab plus chemotherapy was associated with OS benefits at both 18 and 60 months. Sintilimab plus chemotherapy was associated with relatively fewer grade ≥ 3 adverse events than other ICI combination therapies.

CONCLUSION

Our results show that ICI combination therapies showed better survival benefits than chemotherapy. Pembrolizumab plus chemotherapy could provide the best OS benefits to patients with advanced nsq-NSCLC, whereas atezolizumab plus bevacizumab plus chemotherapy could bring the best PFS benefits. The optimal ICI combination therapy varies depending on PD-L1 expression level.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=325005, identifier CRD42022325005.