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On the relationship between tumour growth rate and survival in non-small cell lung cancer.

ABSTRACT: A recurrent question within oncology drug development is predicting phase III outcome for a new treatment using early clinical data. One approach to tackle this problem has been to derive metrics from mathematical models that describe tumour size dynamics termed re-growth rate and time to tumour re-growth. They have shown to be strong predictors of overall survival in numerous studies but there is debate about how these metrics are derived and if they are more predictive than empirical end-points. This work explores the issues raised in using model-derived metric as predictors for survival analyses. Re-growth rate and time to tumour re-growth were calculated for three large clinical studies by forward and reverse alignment. The latter involves re-aligning patients to their time of progression. Hence, it accounts for the time taken to estimate re-growth rate and time to tumour re-growth but also assesses if these predictors correlate to survival from the time of progression. I found that neither re-growth rate nor time to tumour re-growth correlated to survival using reverse alignment. This suggests that the dynamics of tumours up until disease progression has no relationship to survival post progression. For prediction of a phase III trial I found the metrics performed no better than empirical end-points. These results highlight that care must be taken when relating dynamics of tumour imaging to survival and that bench-marking new approaches to existing ones is essential.

SUBMITTER: Mistry HB

PROVIDER: S-EPMC5712205 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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On the relationship between tumour growth rate and survival in non-small cell lung cancer.

Mistry Hitesh B HB

PeerJ 20171129

A recurrent question within oncology drug development is predicting phase III outcome for a new treatment using early clinical data. One approach to tackle this problem has been to derive metrics from mathematical models that describe tumour size dynamics termed re-growth rate and time to tumour re-growth. They have shown to be strong predictors of overall survival in numerous studies but there is debate about how these metrics are derived and if they are more predictive than empirical end-point ...[more]

PMID: 29201573

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Project description:BackgroundThe difference of patients' baseline characteristics such as sex, age, Eastern Cooperative Oncology Group performance status (ECOG PS), and smoking status may influence the immune response. However, little is known about whether these factors affect the efficacy of immune checkpoint inhibitors (ICIs) in patients with advanced non-small-cell lung cancer (NSCLC). Therefore, we performed this systematic review and meta-analysis to investigate the relationship between patients' baseline characteristics and survival benefits in immunotherapy-treated NSCLC.Materials and methodsWe performed a systematic search of PubMed, the Cochrane Library, and Embase for randomized controlled trials (RCTs) of NSCLC immunotherapy. We also searched abstracts and presentations from the proceedings of the American Society of Clinical Oncology and the European Society of Medical Oncology to identify unpublished studies. These studies have available data based on patients' baseline characteristics (such as sex, age, ECOG PS, and smoking status). We take the hazard ratios (HRs) and 95% confidence intervals (CIs) of overall survival (OS) as the effect index and use the random effect model to pool the results.ResultsWe included 18 phase II/III RCTs with a total of 14,189 participants. The benefits of ICIs were found for both male (pooled OS-HR 0.77, 95% CI 0.72-0.82, P < 0.05) and female patients (pooled OS-HR 0.77, 95% CI 0.67-0.87, P < 0.05); for both younger (<65 y: pooled OS-HR 0.74, 95% CI 0.68-0.81, P < 0.05) and older patients (≥65 y: pooled OS-HR 0.80, 95% CI 0.75-0.86, P < 0.05); and for both patients with ECOG PS = 0 (pooled OS-HR 0.77, 95% CI 0.71-0.84, P < 0.05) and ECOG PS ≥ 1 (pooled OS-HR 0.76, 95% CI 0.70-0.82, P < 0.05). Moreover, there was no significant difference in the efficacy of ICIs among different sex (P value for interaction = 0.955), age (P value for interaction = 0.17), or ECOG PS (P value for interaction = 0.765). However, in patients with different smoking status, the application of ICIs significantly prolonged the OS of smokers (pooled OS-HR 0.77, 95% CI 0.71-0.83, P < 0.05) but could not significantly improve the OS of never smokers (pooled OS-HR 0.85, 95% CI 0.70-1.03, P > 0.05).ConclusionsICIs could significantly improve prognosis in patients with advanced NSCLC, regardless of sex, age, or ECOG PS. But among patients with different smoking status, the survival benefits of never smokers treated with ICIs were no better than that of controls. The impact of these factors on immunotherapy should be considered in the future clinical practice and guidelines.

Project description:INTRODUCTION:Alternative predictive end points for overall survival (OS), such as tumor response and progression-free survival (PFS), are useful in the early detection of drug efficacy; however, they have not been fully investigated in patients with advanced NSCLC treated with anti-programmed death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) antibodies. METHODS:In a systematic review of the reported prospective clinical trials, data for response rate, median PFS, and median OS were extracted from 12 arms in 10 reported clinical trials using anti-PD-1/PD-L1 antibody, and their correlation was investigated. In a retrospective analysis at our institution, OS was compared according to tumor response on 5- to 9-week computed tomography scans and status of being progression-free at 8, 16, and 24 weeks by landmark analysis in 71 patients with advanced NSCLC treated with anti-PD-1/PD-L1 antibodies between 2013 and 2015. RESULTS:In a systematic review, moderate correlations between median OS and median PFS (p = 0.120, r = 0.473) and between median OS and response rate (p = 0.141, r = 0.452) were identified using the Spearman correlation coefficient, although these correlations were not statistically significant. In a retrospective analysis of patients treated at our institution, disease control (partial response [PR]/stable disease versus progressive disease/not evaluable), and progression-free status at 8, 16, and 24 weeks significantly predicted OS (Cox proportional hazards model, PR/stable disease versus progressive disease/not evaluable, p = 0.0104, HR = 3.041; 8-week progression-free yes versus no, p = 0.0183, HR = 2.684; 16-week progression-free yes versus no, p = 0.0036, HR = 4.009; and 24-week progression-free yes versus no, p = 0.0002, HR = 12.726). CONCLUSIONS:Both disease control (PR plus stable disease status) and landmark progression-free survival were correlated with OS, with the longer interval landmark PFS being the best predictor of survival in patients with NSCLC treated with anti-PD-1/PD-L1 antibodies.

Dataset Information

On the relationship between tumour growth rate and survival in non-small cell lung cancer.

Publications

On the relationship between tumour growth rate and survival in non-small cell lung cancer.

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