Association Between Toxic Effects and Survival in Patients With Cancer and Autoimmune Disease Treated With Checkpoint Inhibitor Immunotherapy.
Ontology highlight
ABSTRACT:
SUBMITTER: Han CY
PROVIDER: S-EPMC9264212 | biostudies-literature | 2022 Sep
REPOSITORIES: biostudies-literature
Publications
Association Between Toxic Effects and Survival in Patients With Cancer and Autoimmune Disease Treated With Checkpoint Inhibitor Immunotherapy.
Han Catherine Young CY Fitzgerald Conall C Lee Mark M Valero Cristina C Gönen Mithat M Shoushtari Alexander A Morris Luc G T LGT
JAMA oncology 20220901 9
Similar Datasets
Project description:ImportanceImmunotherapy with checkpoint inhibitors targeting the PD-1 (programmed cell death 1) axis has brought notable progress in patients with non-small cell lung cancer (NSCLC) and other cancers. However, autoimmune toxic effects are frequent and poorly understood, making it important to understand the pathophysiologic processes of autoimmune adverse effects induced by checkpoint inhibitor therapy.ObjectiveTo gain mechanistic insight into autoimmune skin toxic effects induced by anti-PD-1 treatment in patients with non-small cell lung cancer.Design, setting, and participantsThis prospective cohort study was conducted from July 1, 2016, to December 31, 2018. Patients (n = 73) with non-small cell lung cancer who received anti-PD-1 therapy (nivolumab or pembrolizumab) were recruited from 4 different centers in Switzerland (Kantonsspital St Gallen, Spital Grabs, Spital Wil, and Spital Flawil). Peripheral blood mononuclear cells, tumor biopsy specimens and biopsies from sites of autoimmune skin toxic effects were collected over a 2-year period, with patient follow-up after 1 year.Main outcomes and measuresResponse to treatment, overall survival, progression-free survival, and development of autoimmune toxic effects (based on standard laboratory values and clinical examinations).ResultsOf the cohort of 73 patients with NSCLC (mean [SD] age, 68.1 [8.9] years; 44 [60%] men), 25 (34.2% [95% CI, 24.4%-45.7%]) developed autoimmune skin toxic effects, which were more frequent in patients with complete remission or partial remission (68.2% [95% CI, 47.3%-83.6%]) than those with progressive or stable disease (19.6% [95% CI, 11.0%-32.5%]) (χ2 = 14.02, P < .001). Nine T-cell antigens shared between tumor tissue and skin were identified. These antigens were able to stimulate CD8+ and CD4+ T cells in vitro. Several of the antigen-specific T cells found in blood samples were also present in autoimmune skin lesions and lung tumors of patients who responded to anti-PD-1 therapy.Conclusions and relevanceThese findings highlight a potential mechanism of checkpoint inhibitor-mediated autoimmune toxic effects and describe the association between toxic effects and response to therapy; such an understanding will help in controlling adverse effects, deciphering new cancer antigens, and further improving immunotherapy.
| S-EPMC6487908 | biostudies-literature
Project description:BackgroundOptimal prognostic biomarkers for patients with gastric cancer who received immune checkpoint inhibitor (ICI) are lacking. Inflammatory markers including lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and systemic inflammation index (SII) are easily available. However, its correlation with ICI is unknown in gastric cancer. Here, we evaluated the potential association between LMR, PLR, and SII with clinical outcomes in gastric cancer patients undergoing ICI therapy.MethodsWe examined LMR, PLR, SII at baseline, and 6 (± 2) weeks later in 139 patients received ICI therapy between August 2015 and April 2019 at Peking University Cancer Hospital (Beijing, China). Landmark analysis at 6 weeks was conducted to explore the prognostic value of LMR, PLR, and SII on progress-free survival (PFS), and overall survival (OS). A Cox proportional hazards model was used to compute mortality hazard ratios (HRs) for LMR, adjusting for potential confounders including age, sex, ECOG, tumor location, tumor differentiation, tumor stage, line of therapy, and type of anti-PD-1/PD-L1 therapy.ResultsAmong 139 patients, 103 (74.1%) were male, median age was 60 years. Median duration of therapy was 6 cycles. We observed that both LMR at baseline and week 6 were independent prognostic factors. Patients with a higher LMR (≥ 3.5) at baseline or week 6 had superior PFS [baseline: HR 0.58, 95% confidence interval (CI): 0.38-0.91; week 6: HR 0.48, 95% CI: 0.29-0.78] and OS (baseline: HR 0.38, 95% CI: 0.24-0.62; week 6: HR 0.52, 95% CI: 0.31-0.88) compared with patients with a lower LMR (< 3.5). Furthermore, for patients with both LMR ≥ 3.5 at baseline and LMR ≥ 3.5 at week 6 were estimated to have much better PFS (HR 0.41, 95% CI: 0.23-0.72) and OS (HR 0.34, 95% CI: 0.18-0.64) than patients with both LMR < 3.5 at baseline and LMR < 3.5 at week 6.ConclusionsBaseline and early changes in LMR were strongly associated with survival in gastric cancer patients who received ICI therapy, and may serve to identify patients most likely to benefit from ICI.
| S-EPMC8203902 | biostudies-literature
Project description:Background and aimsImmune checkpoint inhibitors (ICI) are increasingly used in cancer therapy. Elevated liver enzymes frequently occur in patients treated with ICI but evaluation is poorly described. We sought to better understand causes of liver enzyme elevation, investigation and management.MethodsPatients treated with anti-PD-1, PDL-1 or CTLA-4 therapy in Phase I/II clinical trials between August 2012 and December 2018 were included. Clinical records of patients with significant liver enzyme elevations were retrospectively reviewed.ResultsOf 470 ICI-treated patients, liver enzyme elevation occurred in 102 (21.6%), attributed to disease progression (56; 54.9%), other drugs/toxins (7; 6.9%), other causes (22; 21.6%) and ICI immunotoxicity (17; 16.7%; 3.6% of total cohort). Immunotoxicity was associated with higher peak ALT than other causes of enzyme elevation (N = 17; M = 217, 95% CI 145-324 for immunotoxicity, N = 103; M = 74, 95% CI 59-92 for other causes; ratio of means 0.34, 95% CI 0.19-0.60, p = <0.001) and higher ALT:AST ratio (M = 1.27, 95% CI 0.78-2.06 for immunotoxicity, M = 0.69, 95% CI 0.59-0.80 for other causes, ratio of means 0.54, 95% CI 0.36-0.82, p = 0.004). Immunotoxicity was more often seen in patients with prior CPI exposure (41.2% of immunotoxicity vs 15.9% of patients without, p = 0.01), anti-CTLA-4 -containing ICI treatments (29.4% of immunotoxicity vs 6.8% of patients without, p = <0.001) and other organ immunotoxicity (76.5% of immunotoxicity vs 19.2% of patients without, p = <0.001). Cause for enzyme elevation was established in most patients after non-invasive investigation. Liver biopsy was reserved for four patients with atypical treatment response.ConclusionsLiver enzyme elevation is common in patients receiving ICI, but often has a cause other than immunotoxicity. A biochemical signature with higher ALT and ALT/AST ratio, a history of prior ICI exposure and other organ immunotoxicities may help to identify patients at a higher likelihood of immunotoxicity. Liver biopsy can be safely deferred in most patients. We propose an approach to diagnostic evaluation in patients with liver enzyme elevations following ICI exposure.
| S-EPMC8195413 | biostudies-literature
Project description:We present a mechanistic mathematical model of immune checkpoint inhibitor therapy to address the oncological need for early, broadly applicable readouts (biomarkers) of patient response to immunotherapy. The model is built upon the complex biological and physical interactions between the immune system and cancer, and is informed using only standard-of-care CT. We have retrospectively applied the model to 245 patients from multiple clinical trials treated with anti-CTLA-4 or anti-PD-1/PD-L1 antibodies. We found that model parameters distinctly identified patients with common (n = 18) and rare (n = 10) malignancy types who benefited and did not benefit from these monotherapies with accuracy as high as 88% at first restaging (median 53 days). Further, the parameters successfully differentiated pseudo-progression from true progression, providing previously unidentified insights into the unique biophysical characteristics of pseudo-progression. Our mathematical model offers a clinically relevant tool for personalized oncology and for engineering immunotherapy regimens.
| S-EPMC7190324 | biostudies-literature
Project description:ObjectivesDespite growing evidence that checkpoint inhibitor immunotherapy (IO) toxicity is associated with improved treatment response, the relationship between immune-related adverse events (irAEs) and overall survival (OS) among older adults [age ≥ 70 years (y)] remains unknown. The study goal was to determine differences in OS based on age and ≥ grade 3 (G3) irAEs.Materials and methodsThis was a retrospective cohort study of 673 patients with advanced cancer. Patients who received ≥1 dose of IO at our institution from 2011 to 2018 were eligible. The primary outcome was OS from the start of first line of IO treatment, compared between four patient groups stratified by age and ≥ G3 irAEs with adjustment for patient characteristics using a Cox proportional hazards model.Results and conclusionAmong all 673 patients, 35.4% were ≥ 70y, 39.8% had melanoma, and 45.6% received single-agent nivolumab. Incidence and types of ≥G3 irAEs did not differ by age. Median OS was significantly longer for all patients with ≥G3 irAEs (unadjusted 21.7 vs. 11.9 months, P = 0.007). There was no difference in OS among patients ≥70y with ≥G3 irAEs (HR 0.94, 95% CI 0.61-1.47, P = 0.79) in the multivariable analysis. Patients <70y with ≥G3 irAEs had significantly increased OS (HR 0.33, 95% CI 0.21-0.52, P < 0.001). Younger patients, but not older adults, with high-grade irAEs experience strong survival benefit. This difference may be due to the toll of irAEs themselves or the effects of treatments for irAEs, such as corticosteroids. Factors impacting OS of older adults after irAEs must be determined and optimized.
| S-EPMC8184608 | biostudies-literature
Project description:Immune checkpoint inhibitors (ICIs) with nivolumab and pembrolizumab are promising agents for advanced hepatocellular carcinoma (HCC) but lack of effective biomarkers. We aimed to investigate the potential predictors of response and factors associated with overall survival (OS) for ICI treatment in unresectable HCC patients. Ninety-five patients who received nivolumab or pembrolizumab for unresectable HCC were enrolled for analyses. Radiologic evaluation was based on RECIST v1.1. Factors associated with outcomes were analyzed. Of 90 patients with evaluable images, the objective response rate (ORR) was 24.4%. Patients at Child-Pugh A or received combination treatment had higher ORR. Early alpha-fetoprotein (AFP) >10% reduction (within 4 weeks) was the only independent predictor of best objective response (odds ratio: 7.259, p = 0.001). For patients with baseline AFP ≥10 ng/mL, significantly higher ORR (63.6% vs. 10.2%, p < 0.001) and disease control rate (81.8% vs. 14.3%, p < 0.001) were observed in those with early AFP reduction than those without. In addition, early AFP reduction and albumin-bilirubin (ALBI) grade or Child-Pugh class were independent factors associated with OS in different models. In conclusion, a 10-10 rule of early AFP response can predict objective response and survival to ICI treatment in unresectable HCC. ALBI grade and Child-Pugh class determines survival by ICI treatment.
| S-EPMC7017111 | biostudies-literature
Project description:Checkpoint inhibitors can be a highly effective antitumor therapy but only to a subset of patients, presumably due to immunotherapy resistance. Fluoxetine was recently revealed to inhibit the NLRP3 inflammasome, and NLRP3 inhibition could serve as a target for immunotherapy resistance. Therefore, we evaluated the overall survival (OS) in patients with cancer receiving checkpoint inhibitors combined with fluoxetine. A cohort study was conducted among patients diagnosed with lung, throat (pharynx or larynx), skin, or kidney/urinary cancer treated with checkpoint inhibitor therapy. Utilizing the Veterans Affairs Informatics and Computing Infrastructure, patients were retrospectively evaluated during the period from October 2015 to June 2021. The primary outcome was overall survival (OS). Patients were followed until death or the end of the study period. There were 2316 patients evaluated, including 34 patients who were exposed to checkpoint inhibitors and fluoxetine. Propensity score weighted Cox proportional hazards demonstrated a better OS in fluoxetine-exposed patients than unexposed (HR: 0.59, 95% CI 0.371-0.936). This cohort study among cancer patients treated with checkpoint inhibitor therapy showed a significant improvement in the OS when fluoxetine was used. Because of this study's potential for selection bias, randomized trials are needed to assess the efficacy of the association of fluoxetine or another anti-NLRP3 drug to checkpoint inhibitor therapy.
| S-EPMC10220705 | biostudies-literature
Project description:This protocol describes the application of a mechanistic mathematical model of immune checkpoint inhibitor (ICI) immunotherapy to patient tumor imaging data for predicting solid tumor response and patient survival under ICI intervention. We describe steps for data collection and processing, data pipelines, and approaches to increase precision. The protocol is highly predictive as early as the first restaging after treatment start and can be used with standard-of-care imaging measures. For complete details on the use and execution of this protocol, please refer to Butner et al. (2020)1 and Butner et al. (2021).2.
| S-EPMC9719106 | biostudies-literature
Project description:We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based on both measures that are calculable from mechanistic models of key mechanisms underlying ICI therapy that may not be directly measurable in the clinic and easily measurable quantities or patient characteristics that are not always readily incorporated into predictive mechanistic models. A deep learning time-to-event predictive model trained on a hybrid mechanistic + clinical data set from 93 patients achieved higher per-patient predictive accuracy based on event-time concordance, Brier score, and negative binomial log-likelihood-based criteria than when trained on only mechanistic model-derived values or only clinical data. Feature importance analysis revealed that both clinical and model-derived parameters play prominent roles in increasing prediction accuracy, further supporting the advantage of our hybrid approach.
| S-EPMC11324794 | biostudies-literature
Project description:Aim/introductionAlthough immune checkpoint inhibitor-related type 1 diabetes mellitus (ICI-T1DM) is a rare condition, it is of significant concern globally. We aimed to elucidate the precise incidence, risk factors, and impact of ICI-T1DM on survival outcomes.Materials and methodsThe study is a large retrospective cohort study, performed using the DeSC Japanese administrative claims database comprising 11 million patients. The database population is reportedly similar to the entire population of Japan. Patients administered ICI between 2014 and 2022 were enrolled in the study, including 21,121 patients. The risk factors for ICI-T1DM development and their characteristics were evaluated by logistic regression analysis. Development of a new irAE after the day following the first administration of ICI was set as the study outcome.ResultsICI-T1DM was observed in 102 (0.48%) of the 21,121 patients after ICI initiation. PD-(L)1 and CTLA-4 combination therapy was associated with an increased risk of ICI-T1DM compared with PD-1 monotherapy (odds ratio [OR], 2.36; 95% confidence interval [CI], 1.21-4.58; P = 0.01). Patients with a prior diagnosis of diabetes mellitus (OR, 1.59; 95% CI, 1.03-2.46; P = 0.04) or hypothyroidism (OR, 2.48; 95% CI, 1.39-4.43; P < 0.01) also exhibited an increased risk of ICI-T1DM. The Kaplan-Meier analysis revealed that patients with ICI-T1DM showed higher survival rates than those without (log-lank test, P < 0.01). Multivariable Cox regression analysis demonstrated that ICI-T1DM development was associated with lower mortality (hazard ratio, 0.60; 95% CI, 0.37-0.99; P = 0.04).ConclusionsCollectively, the results of this study demonstrate the precise incidence and risk factors of ICI-T1DM. The development of ICI-T1DM, like other irAEs, is associated with higher survival rates.
| S-EPMC11786175 | biostudies-literature