Pembrolizumab versus the standard of care for cancer therapy: A meta-analysis of 12 KEYNOTE trials comparing overall survival.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14159-e14159 ◽  
Author(s):  
Nathaniel Parker ◽  
Ammar Al-Obaidi ◽  
Quoc Van Truong ◽  
Robert Badgett
Keyword(s):  
Overall Survival ◽  
Cancer Patients ◽  
Checkpoint Inhibitors ◽  
Meta Analysis ◽  
Antineoplastic Agent ◽  
Standard Of Care ◽  
Phase Iii ◽  
Cancer Type ◽  
Random Effects Models ◽  
Phase Iii Trials

e14159 Background: Pembrolizumab (P) is an antineoplastic agent approved for multiple different tumor origins as well as tumor agnostic based on MSI status. Thus understanding the tumor characteristics most predictive of response is essential. Living meta-analysis provides a method to continuously assimilate emerging trials. In this study, we created a living meta-analysis to compare the effect of P on overall survival (OS). Methods: Meta-analysis was conducted according to the PRISMA guidelines. PubMed and Cochrane databases, and conference abstracts (e.g. ASCO, ESMO), were searched for phase III KEYNOTE RCT’s that reported OS among cancer patients receiving P. Results: 12 phase III trials involving 7,319 patients (3,861 in P arms) treated for 6 different types of cancer were retrieved. Median follow up was 12.9 months [range: 0.1-35.5]. Treatment was P alone, SOC chemo, and P + chemo in 11 (40%), 13 (46%), and 4 (14%) arms, respectively. P significantly improved OS (HR 0.71, 95% CI: 0.59-0.85, p <0.001, I2 = 0%) when used in any cancer type, setting, or therapy for advanced refractory or chemo-naïve cancer patients. The mean median OS was 12.5 vs 11.1 months in the total populations for all P and control arms, respectively (Table). Conclusions: Among all trials, P was associated with improved OS. Additional meta-analysis will be performed with R software (version 3.3.3; R Fdn.). Random-effects models will be used to compare OS. Heterogeneity will be assessed with Cochrane Q -statistic and quantified with I2test via subgroup analyses for cancer type, setting, therapy, and PD-L1%. This meta-analysis is continuously updated at http://openmetaanalysis.github.io/checkpoint-inhibitors. [Table: see text]

Nivolumab versus the standard of care for cancer therapy: A meta-analysis of 6 CHECKMATE trials comparing overall survival.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15165-e15165
Author(s):  
Ammar Al-Obaidi ◽  
Nathaniel Parker ◽  
Quoc Van Truong
Keyword(s):  
Overall Survival ◽  
Cancer Patients ◽  
Survival Data ◽  
Meta Analysis ◽  
Antineoplastic Agent ◽  
Standard Of Care ◽  
Phase Iii ◽  
Cancer Type ◽  
Random Effects Models ◽  
Line Setting

e15165 Background: Nivolumab (N) is an antineoplastic agent approved for multiple different tumor origins as well as tumor agnostic based on MSI status. Thus, understanding the tumor characteristics most predictive of response is essential. Living meta-analysis provides a method to continuously assimilate emerging trials. In this study, we created a living meta-analysis to compare the effect of N on overall survival (OS). Methods: Meta-analysis was conducted according to the PRISMA guidelines. PubMed and Cochrane databases, and conference abstracts (e.g. ASCO, ESMO), were searched for phase III CHECKMATE RCT’s that reported OS among cancer patients receiving N. Results: Six phase III trials involving 3,342 patients (1,826 in N arms) treated for 4 different types of cancer were retrieved. Median follow up was 12.1 months [range: 5.1-25.2]. Improved efficacy and safety were observed in all N arms compared to control groups (22.8% ORR; 17.4% grade 3-5 AE vs 15.1% ORR; 51% grade 4-5 AE). Treatment was N alone, SOC chemo, and N + chemo in four (33%), six (50%), and two (16%) arms, respectively. Primary endpoints were OS in the first-line setting in 50% of all arms. Excluding one RCT due to insufficient survival data, the mean median OS was 11.1 [95% CI: 7.5-14.4] vs 8.7 [95% CI: 5.1-13.2] months in the total populations for all N and control arms, respectively. N improved OS when used in any cancer type, setting, or therapy for advanced refractory or chemo-naive cancer patients. Also, efficacy of N was improved with PD-L1% (Table). Conclusions: Among all trials, N was associated with improved OS. Additional meta-analysis is ongoing with R software (version 3.3.3; R Fdn.). Random-effects models will be used to compare OS. Heterogeneity will be assessed with Cochrane Q-statistic and quantified with I2test via subgroup analyses for cancer type, setting, therapy, and PD-L1%. [Table: see text]

Clinical Equipoise for Trials of Novel Biologic Therapies, Therapeutic Success Rates, and Predictors of Success: A Meta-Analysis

2017 ◽  
pp. 1-12
Author(s):  
Doah Cho ◽  
Felicia T. Roncolato ◽  
Johnathan Man ◽  
John Simes ◽  
Sarah J. Lord ◽  
...  
Keyword(s):  
Meta Analysis ◽  
Progression Free Survival ◽  
Standard Of Care ◽  
Phase Iii ◽  
Predictors Of Success ◽  
Biologic Therapies ◽  
Therapeutic Success ◽  
Free Survival ◽  
Randomized Controlled ◽  
Phase Iii Trials

Purpose The demand for more rapid access to novel biologic therapies than randomized controlled trials can deliver is a topic of ongoing study and debate. We aimed to inform this debate by estimating therapeutic success from phase III trials comparing novel biologic therapies with standard of care and identifying predictors of success. Methods This was a meta-analysis of phase III trials evaluating novel biologic therapies in advanced breast, colorectal, lung, and prostate cancers. Therapeutic success was defined as statistically significant results for the primary end point favoring novel biologic therapies. Results Of 119 included phase III trials (76,726 patients), therapeutic success was 41%, with a statistically significant relative reduction in disease progression and death for novel biologic therapies over standard of care of 20% and 8%. Therapeutic success did not improve over time (pre-2010, 33%; 2010 to 2014, 44%; P = .2). Predictors of success were a biomarker-selected population (odds ratio, 4.74; 95% CI, 2.05 to 10.95) and progression-free survival end point compared with overall survival (odds ratio, 5.22; 95% CI, 2.41 to 11.39). Phase III trials with a biomarker-selected population showed a larger 28% progression-free survival benefit than phase III trials overall (hazard ratio, 0.72; 95% CI, 0.70 to 0.75) but similar 8% overall survival benefit (hazard ratio, 0.92; 95% CI, 0.90 to 0.94). Therapeutic success of phase III trials with and without a preceding phase II trial were 43% and 30%, respectively Conclusion Therapeutic success of novel biologic therapies in phase III trials, including therapies with a matching predictive biomarker, was modest and has not significantly improved over time. Equipoise remains and supports the ongoing ethical and scientific requirement for phase III randomized controlled trials to estimate treatment efficacy and assess the value of potential biomarkers.

Comparative analysis of durable responders on immune checkpoint inhibitors (ICI) versus other systemic therapies: A meta-analysis of phase III trials.

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. 3070-3070 ◽  
Author(s):  
Elvire Pons-Tostivint ◽  
Aurélien Latouche ◽  
Pauline Vaflard ◽  
Francesco Ricci ◽  
Delphine Loirat ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Meta Analysis ◽  
Phase Iii ◽  
Phase Iii Trials ◽  
Systemic Therapies

scholarly journals The Significance of SIX1 as a Prognostic Biomarker for Survival Outcome in Various Cancer Patients: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Guang Zhu ◽  
Ying Liu ◽  
Lei Zhao ◽  
Zhenhua Lin ◽  
Yingshi Piao
Keyword(s):  
Systematic Review ◽  
Overall Survival ◽  
Cancer Patients ◽  
Human Cancer ◽  
Meta Analysis ◽  
Disease Free Survival ◽  
Cancer Type ◽  
Free Survival ◽  
Cancer Types ◽  
Disease Free

Sine Oculis Homeobox Homolog 1 (SIX1) is reported to promote cancer initiation and progression in many preclinical models and is demonstrated in human cancer tissues. However, the correlation between SIX1 and cancer patients’ prognosis has not yet been systematically evaluated. Therefore, we performed a systematic review and meta-analysis in various human cancer types and extracted some data from TCGA datasets for further verification and perfection. We constructed 27 studies and estimated the association between SIX1 expression in various cancer patients’ overall survival and verified with TCGA datasets. Twenty-seven studies with 4899 patients are include in the analysis of overall, and disease-free survival, most of them were retrospective. The pooled hazard ratios (HRs) for overall and disease-free survival in high SIX1 expression patients were 1.54 (95% CI: 1.32-1.80, P&lt;0.00001) and 1.83 (95% CI: 1.31-2.55, P=0.0004) respectively. On subgroup analysis classified in cancer type, high SIX1 expression was associated with poor overall survival in patients with hepatocellular carcinoma (HR 1.50; 95% CI: 1.17-1.93, P =0.001), breast cancer (HR 1.31; 95% CI: 1.10-1.55, P =0.002) and esophageal squamous cell carcinoma (HR 1.89; 95% CI: 1.42-2.52, P&lt;0.0001). Next, we utilized TCGA online datasets, and the consistent results were verified in various cancer types. SIX1 expression indicated its potential to serve as a cancer biomarker and deliver prognostic information in various cancer patients. More works still need to improve the understandings of SIX1 expression and prognosis in different cancer types.

scholarly journals Association of Immune Related Adverse Events With Efficacy of Immune Checkpoint Inhibitors and Overall Survival in Cancers: A Systemic Review and Meta-analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Yong Fan ◽  
Wenhui Xie ◽  
Hong Huang ◽  
Yunxia Wang ◽  
Guangtao Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
Adverse Events ◽  
Cancer Patients ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Tumor Response ◽  
Checkpoint Inhibitors ◽  
Meta Analysis ◽  
Pooled Data ◽  
Cancer Types

ObjectivesImmune checkpoint inhibitors (ICIs) have brought impressive benefits to cancer patients, however often accompanied with immune-related adverse events (irAEs). We aimed to investigate the association of irAEs with efficacy and overall survival in cancer patients treated by ICIs, and further quantify the association by stratifying subgroups.MethodsPubMed, EMBASE and Cochrane library from database inception to 29 August 2019 were systematically searched. Articles reporting association of objective response rate (ORR), progression-free survival (PFS), overall survival (OS) with irAEs in cancer patients treated with approved ICIs were included. Adjusted odds ratios (OR) with 95% confidential intervals (CIs) were calculated for ORR, and hazard ratios (HR) were used for PFS and OS.ResultsA total of 52 articles comprising 9,156 patients were included. Pooled data demonstrated a statistically significant greater probability of achieving objective tumor response for patients with irAEs compared to those without (OR 3.91, 95% CI 3.05–5.02). In overall meta-analysis, patients who developed irAEs presented a prolonged PFS (HR 0.54; 95% CI 0.46–0.62) and OS (HR 0.51; 95% CI 0.41–0.59). More specifically, irAEs in certain cancer types (NSCLC and melanoma) and organs (skin and endocrine) were robustly associated with better clinical outcomes, while this association needs further verification regarding other tumors. High grade toxicities (G3–5) were not associated with a significantly favorable PFS or OS. Additionally, the association between irAEs and clinical benefit seemed to be more definite in patients receiving PD-(L)1 blockade than CTLA-4 blockade. Pooled data from landmark analyses displayed consistent results.ConclusionsThe occurrence of irAEs predicted improved tumor response and better survival in overall cancer patients treated with ICIs. Notably, the association stayed robust in certain cancer types (NSCLC and melanoma) and organ-specific irAEs (skin and endocrine).

Clinical significance of tumour mutation burden in immunotherapy across multiple cancer types: an individual meta-analysis

2020 ◽  
Vol 50 (9) ◽  
pp. 1023-1031
Author(s):  
Zhenyu Yang ◽  
Shiyou Wei ◽  
Yulan Deng ◽  
Zihuai Wang ◽  
Lunxu Liu
Keyword(s):  
Overall Survival ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Response Rate ◽  
Checkpoint Inhibitors ◽  
Meta Analysis ◽  
Progression Free Survival ◽  
Cancer Type ◽  
Free Survival ◽  
Mutation Burden

Abstract Background Biomarkers for stratifying patients that could benefit from immune checkpoint inhibitors are necessary. Tumour mutation burden has recently become a promising biomarker in cancer, but the associations between tumour mutation burden and outcomes of immune checkpoint inhibitors treatment were not well-documented in present studies. Methods We searched PubMed, Web of Science and EMBASE databases up to 1 October 2019. Studies evaluated the association between tumour mutation burden and clinical outcomes were included. Hazard ratios and odds ratios were applied to estimate the association of tumour mutation burden score with overall survival, progression-free survival and response rate, respectively. The best cut-off value was chosen by best discriminated overall survival using Contal and O’Quigley method. Results Twenty-two studies involving 6171 patients in diverse cancers were included. The individual participant data meta-analysis demonstrated that high tumour mutation burden was associated with better overall survival (HR = 0.57, 95% CI = 0.50–0.64) and progression-free survival (HR = 0.50, 95% CI = 0.40–0.63) and higher response rate. The best cut-off values in each cancer type were 17.7/MB in non-small cell lung cancer, 7.9/MB in bladder cancer, 6.1/MB in melanoma, 12.3/MB in colorectal cancer, 6.9/MB in esophagogastric cancer, 10.5/MB in head and neck cancer. The pooled meta-analysis showed the prognosis value was robust and the sensitivity, specificity and area under the receiver operating characteristic curves in predicting response rates were 0.63, 0.71 and 0.73, respectively. Conclusions The present meta-analysis indicates tumour mutation burden is a promising predictor of immune checkpoint inhibitors therapy but the cut-off value differs in different cancers.

Sign in / Sign up

Export Citation Format

Share Document