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Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet.

ABSTRACT: We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent at Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, were collected from a retrospective cohort of patients diagnosed in 2004-2014. Patients were followed-up, for three years. Clinical data collected include complete information about the clinical course of the patients including treatment schedule, response according to RECIST classification, and survival. The core of the platform is the mathematical model, in the form of a system of ordinary differential equations, describing dynamics of platinum-sensitive and platinum-resistant cancer cells and interactions reflecting competition for space and resources. The model is simulated stochastically by sampling the parameter values from a joint probability distribution function. The machine learning model is applied to calibrate the mathematical model and to fit it to the overall survival curve. The model simulations faithfully reproduce the clinical cohort at three levels long-term response (OS), the initial response (according to RECIST criteria), and the relationship between the number of chemotherapy cycles and time between two consecutive chemotherapy cycles. In addition, we investigated the relationship between initial and long-term response. We showed that those two variables do not correlate which means that we cannot predict patient survival solely based on the initial response. We also tested several chemotherapy schedules to find the best one for patients treated with palliative intent. We found that the optimal treatment schedule depends, among others, on the strength of competition among various subclones in a tumor. The computational platform developed allows optimizing chemotherapy protocols, within admissible limits of toxicity, for palliative treatment of metastatic NSCLC. The simplicity of the method allows its application to chemotherapy optimization in different cancers.

SUBMITTER: Kozlowska E

PROVIDER: S-EPMC7561182 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet.

Kozłowska Emilia E Suwiński Rafał R Giglok Monika M Świerniak Andrzej A Kimmel Marek M

PLoS computational biology 20201005 10

We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent at Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, were collected from a retrospective cohort of patients diagnosed in ...[more]

PMID: 33017420

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Project description:PurposeNivolumab, a fully human immunoglobulin G4 programmed death-1 immune checkpoint inhibitor antibody, has demonstrated improved survival in previously treated patients with advanced non-small-cell lung cancer (NSCLC). CheckMate 012, a phase I, multicohort study, was conducted to explore the safety and efficacy of nivolumab as monotherapy or combined with current standard therapies in first-line advanced NSCLC. Here, we report results for nivolumab plus platinum-based doublet chemotherapy (PT-DC).Patients and methodsPatients (N = 56) received nivolumab (intravenously) plus PT-DC concurrently every 3 weeks for four cycles followed by nivolumab alone until progression or unacceptable toxicity. Regimens were nivolumab 10 mg/kg plus gemcitabine-cisplatin (squamous) or pemetrexed-cisplatin (nonsquamous) or nivolumab 5 or 10 mg/kg plus paclitaxel-carboplatin (all histologies). The primary objective was to assess safety and tolerability. Secondary objectives included objective response rate and 24-week progression-free survival rate (per Response Evaluation Criteria in Solid Tumors version 1.1); exploratory objectives included overall survival (OS) and response by tumor programmed death ligand-1 expression.ResultsNo dose-limiting toxicities occurred during the first 6 weeks of treatment. Forty-five percent of patients (25 of 56 patients) reported grade 3 or 4 treatment-related adverse events (AEs); 7% of patients (n = 4) had pneumonitis. Twenty-one percent of patients (n = 12) discontinued all study therapy as a result of treatment-related AEs. Objective response rates for nivolumab 10 mg/kg plus gemcitabine-cisplatin, nivolumab 10 mg/kg plus pemetrexed-cisplatin, nivolumab 10 mg/kg plus paclitaxel-carboplatin, and nivolumab 5 mg/kg plus paclitaxel-carboplatin were 33%, 47%, 47%, and 43%, respectively; 24-week progression-free survival rates were 51%, 71%, 38%, and 51%, respectively; 2-year OS rates were 25%, 33%, 27%, and 62%, respectively. Responses were achieved regardless of tumor programmed death ligand-1 expression.ConclusionThe safety profile of nivolumab plus PT-DC was consistent with that expected for individual agents; however, treatment discontinuation related to AEs was greater with the combination. Encouraging activity was observed, especially for the nivolumab 5 mg/kg plus paclitaxel-carboplatin group, with a 2-year OS rate of 62%.

Project description:AimAccurate causality assessment (CA) of adverse events (AEs) is important in clinical research and routine clinical practice. The Naranjo scale (NS) used for CA lacks specificity, leading to a high rate of false positive causal associations. NS is a simple scale for CA; however, its limitations have reduced its popularity in favour of other scales. We therefore attempted to improvise the algorithm by addressing specific lacunae in NS.MethodsWe attempted to modify the existing NS by (a) changing the weightage given to certain responses, (b) achieving higher resolution to certain responses for delineating drug related and unrelated AEs and (c) modifying the slabs for classification of association as 'likely' and 'unlikely'. The new scale, named as the Sharma-Nookala-Gota (SNG) algorithm, was evaluated in a training set of 19 AEs in a tertiary care cancer hospital in western India, and further validated in a set of 104 AEs. Consensus of four physician opinion was taken as gold standard for comparison.ResultsOf the 19 AEs in the training set, 6 were described by the treating physician as 'not related' and 13 as related to the drug. The SNG algorithm had 100% concordance with physician opinion, whereas the NS had only 73.7% concordance. NS showed a tendency to misclassify AEs as 'related' when they were indeed 'not related'. In the validation set of 104 AEs, NS and SNG algorithms misclassified 30 and 2 AEs, respectively, leading to a concordance of 70.2% and 98.1%, respectively, with physician opinion.ConclusionDecisive modifications of the NS resulted in the SNG scale, with superior specificity while retaining sensitivity against the gold standard.Plain language summarySNG algorithm - A novel tool for causality assessment of adverse drug reactions Adverse events (AEs) can cause increased morbidity, hospitalisation, and even death. Hence it is essential to recognise AEs and to establish their correct causal relationship to a drug. Many causality assessment methods, scales and algorithms are available to assess the relationship between an AE and a drug. The Naranjo algorithm is most commonly employed in spite of its many drawbacks as it is simple to use. Concerns have been raised regarding the performance of the scale, and researchers have tried to answer them, but none of them could address all issues satisfactorily. We too experienced many problems while using it in our routine clinical practice and in clinical trials. For instance, the Naranjo scale is non-specific and shows a bias toward implicating the drug as the causal factor for AEs. This improper assessment has often led to drug discontinuation, thereby compromising the efficacy of treatment. Hence, we modified the existing Naranjo scale to a new one (the Sharma-Nookala-Gota - SNG algorithm) to address these shortcomings. We piloted the SNG causality assessment algorithm in patients suffering from AEs due to various drugs. The SNG algorithm was found to have good concordance with the physicians' assessment of causality. As a next step, we validated the SNG algorithm in patients receiving a standard drug combination of pemetrexed and carboplatin for lung cancer combination. Out of the 104 AEs observed in 65 patients, the SNG causality assessment algorithm showed good concordance (except in two cases) with the physicians' decision of causality assessment, while the Naranjo algorithm was not so successful. Hence, the SNG algorithm can be a better guide for causality assessment of AEs.

Project description:BackgroundDoublet platin-chemotherapy was the old standard treatment for different histology types of advanced and metastatic lung cancer (LC) and is still an option for patients who are not eligible for immune checkpoint inhibitors. However, in low- and middle-income countries, chemotherapy, either in monotherapy or in combination with platinum, is still the only accessible option in public institutions. The efficacy of different platin-based chemotherapy in patients with LC who are treatment-naïve is unknown.MethodsIn this retrospective study, we selected patients with advanced and metastatic (IIIB-IVB) non-squamous non-small cell LC (NSCLC), squamous NSCLC, and lung neuroendocrine tumours (small cell LC (SCLC), large cell neuroendocrine, and atypical carcinoid) aged beyond 18 years who received first-line chemotherapy (docetaxel, gemcitabine, etoposide, paclitaxel, pemetrexed, and vinorelbine) combined with platinum between January 1, 2013, and December 31, 2022. Within the population with non-squamous NSCLC, squamous NSCLC, and neuroendocrine tumours, progression-free survival (PFS) and overall survival (OS) were the primary assessed endpoints. Hematologic safety was the secondary endpoint.ResultsOverall, 611 patients were included. In the group of patients with non-squamous NSCLC (n = 390), there was no statistical difference between subgroups of patients who received first-line platin-chemotherapy. The median PFS was 182 (95 % confidence interval [CI], 167-208) days (hazard ratio for progression: NR [Not Reached]; p = 0.37), and the median OS was 446 (95 % CI, 405-559) days (hazard ratio for death: 1.31; 95 % CI, 0.94 - 1.82; p = 0.1). In the group of patients with squamous NSCLC (n = 149), we note the absence of statistical significance between subgroups of patients who received platin-based chemotherapy. The median PFS was 195 (95 % CI, 142-238; hazard ratio for progression: 1.21, 95 % CI, 0.29-5.02; p = 0.27), while the median OS was 428 (95 % CI, 324-940) days (hazard ratio for death: 1.76; 95 % CI, 0.93 to 3.3; p = 0.32). The absence of significance has been noticed in the neuroendocrine subgroup of patients who received first etoposide-platinum, vinorelbine-platinum, or paclitaxel-platinum (n = 72). The median PFS was 216 (95 % CI, 193-277) days; hazard ratio for progression: 1.74, 95 % CI, 0.41-7.27; p = 0.69, while the median OS was 273 (95 % CI, 241-459) days (hazard ratio for death: 2.95; 95 % CI, 0.4-21.7; p = 0.51). Grade 3-4 neutropenia grade was the predominant adverse event associated with chemotherapy in almost 11 % of patients.ConclusionMoving forward, treatment strategies must be refined for patients, with an emphasis on increasing the number of patients who can benefit from emergent approaches in order to guarantee a wider, deeper, and longer-lasting outcome.

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Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet.

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Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet.

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