Association Between Body Mass Index and Survival Outcomes In Patients Treated With Immune Checkpoint Inhibitors: Meta-analyses of Individual Patient Data.
Journal
Journal of immunotherapy (Hagerstown, Md. : 1997)
ISSN: 1537-4513
Titre abrégé: J Immunother
Pays: United States
ID NLM: 9706083
Informations de publication
Date de publication:
Historique:
received:
12
03
2021
accepted:
21
07
2021
pubmed:
31
8
2021
medline:
12
2
2022
entrez:
30
8
2021
Statut:
ppublish
Résumé
Despite that immune checkpoint inhibitors (ICIs) had tremendous improved the survival of multiple solid tumors, only a limited proportion of patients are responsive to ICIs. Therefore, effective variables are urgently needed to predict the probability of response to ICIs. Systematic searches were conducted from inception up to May, 2020. Prospective or retrospective studies of ICIs that investigated the association between body mass index (BMI) and survival outcomes, including overall survival (OS) and/or progression-free survival (PFS), were selected. The association between each BMI category and survival outcomes was calculated using Cox proportional hazard regression models and quantified as hazard ratio (HR) with corresponding 95% confidence interval. Seven clinical studies involving data from 3768 individual patients were included. The median OS was 15.5 months (95% confidence interval: 14.7-16.2 mo) and the median PFS was 5.7 months (5.2-6.3 mo). The median OS was significantly longer in overweight/obese patients than in nonoverweight patients (20.7 vs. 11.3 mo; P<0.001). The difference in OS between overweight and obese patients was not statistically significant (HR: 1.14, P=0.098). Similar results were observed for PFS outcomes. Subgroup analysis demonstrated improved OS in overweight/obese patients with nonsmall-cell lung cancer (HR: 0.81, P=0.002), melanoma (HR: 0.66, P<0.001), renal cell carcinoma (HR: 0.53, P<0.001), and multiple cancer type (HR: 0.34, P<0.001), with parallel results noted regarding PFS outcomes. Results of the present study suggested that BMI may be a satisfactory prognostic factor for patients treated with ICIs.
Identifiants
pubmed: 34456293
doi: 10.1097/CJI.0000000000000389
pii: 00002371-202111000-00006
pmc: PMC8500279
doi:
Substances chimiques
Immune Checkpoint Inhibitors
0
Types de publication
Journal Article
Meta-Analysis
Langues
eng
Sous-ensembles de citation
IM
Pagination
371-375Informations de copyright
Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc.
Références
Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012;12:252–264.
Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. Science. 2018;359:1350–1355.
Tang J, Shalabi A, Hubbard-Lucey VM. Comprehensive analysis of the clinical immuno-oncology landscape. Ann Oncol. 2018;29:84–91.
Sanmamed MF, Chen L. A paradigm shift in cancer immunotherapy: from enhancement to normalization. Cell. 2018;175:313–326.
Nie RC, Zhao CB, Xia XW, et al. The efficacy and safety of PD-1/PD-L1 inhibitors in combination with conventional therapies for advanced solid tumors: a meta-analysis. Biomed Res Int. 2020;2020:5059079.
Cristescu R, Mogg R, Ayers M, et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science. 2018;362:eaar3593.
Luksza M, Riaz N, Makarov V, et al. A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy. Nature. 2017;551:517–520.
Le DT, Durham JN, Smith KN, et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357:409–413.
Hugo W, Zaretsky JM, Sun L, et al. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell. 2016;165:35–44.
Rizvi NA, Hellmann MD, Snyder A, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348:124–128.
Hopkins AM, Rowland A, Kichenadasse G, et al. Predicting response and toxicity to immune checkpoint inhibitors using routinely available blood and clinical markers. Br J Cancer. 2017;117:913–920.
Renehan AG, Tyson M, Egger M, et al. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008;371:569–578.
Sepesi B, Gold KA, Correa AM, et al. The influence of body mass index on overall survival following surgical resection of non–small cell lung cancer. J Thorac Oncol. 2017;12:1280–1287.
Caan BJ, Meyerhardt JA, Kroenke CH, et al. Explaining the obesity paradox: the association between Body Composition and Colorectal Cancer Survival (C-SCANS Study). Cancer Epidemiol Biomarkers Prev. 2017;26:1008–1015.
Park SH, Lee S, Song JH, et al. Prognostic significance of body mass index and prognostic nutritional index in stage II/III gastric cancer. Eur J Surg Oncol. 2020;46:620–625.
McQuade JL, Daniel CR, Hess KR, et al. Association of body-mass index and outcomes in patients with metastatic melanoma treated with targeted therapy, immunotherapy, or chemotherapy: a retrospective, multicohort analysis. Lancet Oncol. 2018;19:310–322.
Kichenadasse G, Miners JO, Mangoni AA, et al. Association between body mass index and overall survival with immune checkpoint inhibitor therapy for advanced non-small cell lung cancer. JAMA Oncol. 2020;6:512–518.
Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339:b2700.
Ichihara E, Harada D, Inoue K, et al. The impact of body mass index on the efficacy of anti-PD-1/PD-L1 antibodies in patients with non-small cell lung cancer. Lung Cancer. 2020;139:140–145.
Cortellini A, Bersanelli M, Buti S, et al. A multicenter study of body mass index in cancer patients treated with anti-PD-1/PD-L1 immune checkpoint inhibitors: when overweight becomes favorable. J Immunother Cancer. 2019;7:57.
De Giorgi U, Procopio G, Giannarelli D, et al. Association of systemic inflammation index and body mass index with survival in patients with renal cell cancer treated with nivolumab. Clin Cancer Res. 2019;25:3839–3846.
Labadie BW, Liu P, Bao RY, et al. BMI, irAE, and gene expression signatures associate with resistance to immune-checkpoint inhibition and outcomes in renal cell carcinoma. J Transl Med. 2019;17:386.
Naik GS, Waikar SS, Johnson AEW, et al. Complex inter-relationship of body mass index, gender and serum creatinine on survival: exploring the obesity paradox in melanoma patients treated with checkpoint inhibition. J Immunother Cancer. 2019;7:89.
Chen DS, Mellman I. Elements of cancer immunity and the cancer-immune set point. Nature. 2017;541:321–330.
Martinez-Useros J, Garcia-Foncillas J. Obesity and colorectal cancer: molecular features of adipose tissue. J Transl Med. 2016;14:21.
Zhang Y, Sowers JR, Ren J. Targeting autophagy in obesity: from pathophysiology to management. Nat Rev Endocrinol. 2018;14:356–376.
Olson OC, Quail DF, Joyce JA. Obesity and the tumor microenvironment. Science. 2017;358:1130–1131.
Wang ZM, Aguilar EG, Luna JI, et al. Paradoxical effects of obesity on T cell function during tumor progression and PD-1 checkpoint blockade. Nat Med. 2019;25:141–151.
Liu X, Bao X, Hu M, et al. Inhibition of PCSK9 potentiates immune checkpoint therapy for cancer. Nature. 2020;588:693–698.