Dataset Information

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer.

ABSTRACT:

Background

Immune checkpoint inhibitors (ICIs) plus chemotherapy improved the prognosis of patients with non-small cell lung cancer (NSCLC); however, reliable prognostic biomarkers are lacking. We explored factors associated with prognosis and developed a predictive model.

Methods

We retrospectively analyzed 130 consecutive stage IIIA-IVB NSCLC patients treated with ICIs combined with chemotherapy. Cox univariate and multivariate proportional hazards regression analyses were used to identify prognostic factors associated with progression-free survival (PFS). A nomogram was developed based on key factors in the training cohort (n = 86) and evaluated in the validation cohort (n = 44). According to the nomogram-based total point scores, we divided patients into low- and high-risk groups.

Results

In the training cohort, bone metastases (p = 0.017) and an increased derived neutrophil-to-lymphocyte ratio (p = 0.018) were significantly associated with poor PFS, while smoking (p = 0.007) and programmed death-ligand 1 (PD-L1) ≥50% (p = 0.001) were associated with improved PFS. A nomogram based on these factors was developed to predict PFS at 3, 6, and 12 months. The C-index of the nomogram to predict PFS was 0.725 (95% CI: 0.711-0.739) in the training cohort and 0.688 (95% CI: 0.665-0.711) in the validation cohort. The area under the curve (AUC) exhibited an acceptable discriminative ability, and calibration curves demonstrated a consistency between the actual results and predictions. In the training cohort, the median PFS (mPFS) was 12.3 and 5.7 months in the low- and high-risk groups, respectively (p < 0.001). In the validation cohort, the mPFS was 12.6 and 6.2 months in the low- and high-risk groups, respectively (p = 0.021).

Conclusions

A predictive nomogram was developed to help clinicians assess prognosis early for advanced NSCLC patients who received ICI plus chemotherapy.

SUBMITTER: Zeng H

PROVIDER: S-EPMC8397581 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer.

Zeng Hao H Huang Wei-Wei WW Liu Yu-Jie YJ Huang Qin Q Zhao Sheng-Min SM Li Ya-Lun YL Tian Pan-Wen PW Li Wei-Min WM

Frontiers in oncology 20210812

<h4>Background</h4>Immune checkpoint inhibitors (ICIs) plus chemotherapy improved the prognosis of patients with non-small cell lung cancer (NSCLC); however, reliable prognostic biomarkers are lacking. We explored factors associated with prognosis and developed a predictive model.<h4>Methods</h4>We retrospectively analyzed 130 consecutive stage IIIA-IVB NSCLC patients treated with ICIs combined with chemotherapy. Cox univariate and multivariate proportional hazards regression analyses were used ...[more]

PMID: 34458139

Similar Datasets

Project description:BackgroundLimited data exists on the efficacy of immune checkpoint inhibitor (ICI) combinations in non-small-cell lung cancer (NSCLC) with uncommon driver alterations in genes such as ERBB2, BRAF, RET, and MET. This study retrospectively assessed ICI-combination therapy outcomes in this molecular subset of NSCLC.MethodsWe retrospectively analyzed patients with advanced NSCLC confirmed with driver alterations in genes including ERBB2, BRAF, RET or MET, and received ICI combined with chemotherapy (ICI + chemo) and/or targeted therapy (ICI + chemo/TT) as first-line (1L) or second- or third-line (≥ 2L) treatment at Hunan Cancer Hospital between January 2018 and May 2024.ResultsOf the 181 patients included in the study, 131 patients received 1L-ICI + chemo (ERBB2, n = 64; BRAF, n = 34; RET, n = 23; and MET, n = 10), and 50 patients received ≥ 2L-ICI + chemo/TT (ERBB2, n = 16; BRAF, n = 7; RET, n = 14; MET, n = 13). The full cohort had an overall response rate (ORR) of 45.9% and disease control rate of 84.0%. Among patients who received 1L-ICI + chemo, ORR ranged between 51.6% and 60.0%, with the median progression-free survival (mPFS) and overall survival (mOS) of 8.2 and 21.0 months for those with ERBB2-altered tumors, 10.0 and 15.0 months for BRAF-altered tumors, 12.1 months and OS not reached for RET-altered tumors, and 6.2 and 28.0 months for MET-altered tumors, respectively. Additionally, ORR ranged between 14.3% and 30.8% for ≥ 2L-ICI + chemo/TT; mPFS and mOS were 5.4 and 16.2 months for patients with ERBB2-altered tumors, 2.7 and 5.0 months for BRAF-altered tumors, 6.2 and 14.3 months for RET-altered tumors, and 5.7 and 11.5 months for MET-altered tumors, respectively.ConclusionICI-based combination therapies, regardless of treatment line, were effective in treating patients with advanced NSCLC harboring driver alterations in ERBB2, BRAF, RET, or MET. This suggests their potential as alternative treatment options in this patient population.

Project description:BackgroundThe increasing utilization of immune checkpoint inhibitors (ICIs) has led to a concomitant rise in the incidence of immune-related adverse events (irAEs), notably immune-mediated colitis (IMC). This study aimed to identify the clinical risk factors associated with IMC development in patients with lung cancer and to develop a risk prediction model to facilitate personalized treatment and care strategies.MethodsThe data collected included 21 variables, including sociodemographic characteristics, cancer-related factors, and routine blood markers. The dataset was randomly partitioned into a training set (70%) and a validation set (30%). Univariate and multivariate logistic regression analyses were conducted to identify independent predictors of IMC development. On the basis of the results of the multivariate analysis, a nomogram prediction model was developed. Model performance was assessed via the area under the receiver operating characteristic curve (AUC), calibration curve analysis, decision curve analysis (DCA), and clinical impact curve (CIC).ResultsAmong the 2103 patients, 66 (3.14%) developed IMCs. Multivariate logistic regression analysis revealed female sex, small cell lung cancer (SCLC), elevated β2 microglobulin (β2-MG) and globulin (GLB) levels, and an increased neutrophil-lymphocyte ratio (NLR) as independent predictors of IMC development (all P < 0.05). Conversely, a higher white blood cell (WBC) count, CD4/CD8 ratio, and platelet-lymphocyte ratio (PLR) were identified as factors associated with a reduced risk of IMC development (all P < 0.05). The nomogram prediction model demonstrated good discrimination, achieving an AUC of 0.830 (95% CI: 0.774-0.887) in the training set and 0.827 (95% CI: 0.709-0.944) in the validation set. Analysis of the calibration curve, DCA, and CIC indicated good predictive accuracy and clinical utility of the developed model.ConclusionThis study identified eight independent predictors of IMC development in patients with lung cancer and subsequently developed a nomogram-based prediction model to assess IMC risk. Utilization of this model has the potential to assist clinicians in implementing appropriate preventive and therapeutic strategies, ultimately contributing to a reduction in the incidence of IMC among this patient population.

Project description:ObjectiveTo determine the cost-effectiveness of imported immune checkpoint inhibitors (ICIs) such as atezolizumab and durvalumab, and domestic ICIs like serplulimab and adebrelimab, in combination with chemotherapy for extensive-stage small cell lung cancer (ES-SCLC) in China.MethodsUsing a 21-day cycle length and a 20-year time horizon, a Markov model was established to compare the clinical and economic outcomes of five first-line ICIs plus chemotherapy versus chemotherapy alone, as well as against each other, from the perspective of the Chinese healthcare system. Transition probabilities were estimated by combining the results of the CAPSTONE-1 trial and a published network meta-analysis. Cost and health state utilities were collected from multiple sources. Both cost and effectiveness outcomes were discounted at a rate of 5% annually. The primary model output was incremental cost-effectiveness ratios (ICERs). A series of sensitivity analyses were preformed to assess the robustness of the model.ResultsIn the base-case analysis, the addition of first-line ICIs to chemotherapy resulted in the ICERs ranged from $80,425.31/QALY to $812,415.46/QALY, which exceeded the willing-to-pay threshold set for the model. When comparing these first-line immunochemotherapy strategies, serplulimab plus chemotherapy had the highest QALYs of 1.51286 and the second lowest costs of $60,519.52, making it is the most cost-effective strategy. Our subgroup-level analysis yielded results that are consistent with the base-case analysis. The sensitivity analysis results confirmed the validity and reliability of the model.ConclusionIn China, the combination of fist-line ICIs plus chemotherapy were not considered cost-effective when compared to chemotherapy alone. However, when these fist-line immunochemotherapy strategies were compared with each other, first-line serplulimab plus chemotherapy consistently demonstrated superiority in terms of cost-effectiveness. Reducing the cost of serplulimab per 4.5 mg/kg would be a realistic step towards making first-line serplulimab plus chemotherapy more accessible and cost-effective.

Dataset Information

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer.

Background

Methods

Results

Conclusions

Publications

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets