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A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.

ABSTRACT: Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can overcome this but are currently lacking. A DSS for stage III NSCLC requires the development and integration of multiple models. The current study takes the first step in this process by developing and validating a model that can provide physicians with a survival probability for an individual NSCLC patient.Data from 548 patients with stage III NSCLC were available to enable the development of a prediction model, using stratified Cox regression. Variables were selected by using a bootstrap procedure. Performance of the model was expressed as the c statistic, assessed internally and on 2 external data sets (n=174 and n=130).The final multivariate model, stratified for treatment, consisted of age, gender, World Health Organization performance status, overall treatment time, equivalent radiation dose, number of positive lymph node stations, and gross tumor volume. The bootstrapped c statistic was 0.62. The model could identify risk groups in external data sets. Nomograms were constructed to predict an individual patient's survival probability (www.predictcancer.org). The data set can be downloaded at https://www.cancerdata.org/10.1016/j.ijrobp.2015.02.048.The prediction model for overall survival of patients with stage III NSCLC highlights the importance of combining patient, clinical, and treatment variables. Nomograms were developed and validated. This tool could be used as a first building block for a decision support system.

SUBMITTER: Oberije C

PROVIDER: S-EPMC4786012 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.

Oberije Cary C De Ruysscher Dirk D Houben Ruud R van de Heuvel Michel M Uyterlinde Wilma W Deasy Joseph O JO Belderbos Jose J Dingemans Anne-Marie C AM Rimner Andreas A Din Shaun S Lambin Philippe P

International journal of radiation oncology, biology, physics 20150430 4

<h4>Purpose</h4>Although patients with stage III non-small cell lung cancer (NSCLC) are homogeneous according to the TNM staging system, they form a heterogeneous group, which is reflected in the survival outcome. The increasing amount of information for an individual patient and the growing number of treatment options facilitate personalized treatment, but they also complicate treatment decision making. Decision support systems (DSS), which provide individualized prognostic information, can ove ...[more]

PMID: 25936599

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Project description:PurposeTo test, in a single-arm, prospective, phase 2 trial, whether adding the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor erlotinib to concurrent chemoradiotherapy for previously untreated, locally advanced, inoperable non-small cell lung cancer would improve survival and disease control without increasing toxicity.Methods and materialsForty-eight patients with previously untreated non-small cell lung cancer received intensity modulated radiation therapy (63 Gy/35 fractions) on Monday through Friday, with chemotherapy (paclitaxel 45 mg/m², carboplatin area under the curve [AUC] = 2) on Mondays, for 7 weeks. All patients also received the EGFR tyrosine kinase inhibitor erlotinib (150 mg orally 1/d) on Tuesday-Sunday for 7 weeks, followed by consolidation paclitaxel-carboplatin. The primary endpoint was time to progression; secondary endpoints were overall survival (OS), toxicity, response, and disease control and whether any endpoint differed by EGFR mutation status.ResultsOf 46 patients evaluable for response, 40 were former or never-smokers, and 41 were evaluable for EGFR mutations (37 wild-type [WT] and 4 mutated [all adenocarcinoma]). Median time to progression was 14.0 months and did not differ by EGFR status. Toxicity was acceptable (no grade 5, 1 grade 4, 11 grade 3). Twelve patients (26%) had complete responses (10 WT, 2 mutated), 27 (59%) partial (21 WT, 2 mutated, 4 unknown), and 7 (15%) none (6 WT, 2 mutated, 1 unknown) (P=.610). At 37.0 months' follow-up (range, 3.6-76.5 months) for all patients, median OS time was 36.5 months, and 1-, 2-, and 5-year OS rates were 82.6%, 67.4%, and 35.9%, respectively; none differed by mutation status. Twelve patients had no progression, and 34 had local and/or distant failure. Eleven of 27 distant failures were in the brain (7 WT, 3 mutated, 1 unknown).ConclusionsToxicity and OS were promising, but time to progression did not meet expectations. The prevalence of distant failures underscores the need for effective systemic therapy.

Project description:BackgroundHistorically, the standard of care for patients with unresectable, Stage III non-small cell lung cancer had been concurrent chemoradiotherapy. However, outcomes had been poor, with approximately 15% to 32% of patients alive at 5 years. In the placebo-controlled Phase III A PACIFIC trial, consolidation treatment with durvalumab after concurrent chemoradiotherapy significantly improved overall survival (OS) and progression-free survival in patients with unresectable, Stage III non-small cell lung cancer, establishing this regimen as a new standard of care in this setting. In the PACIFIC trial, crossover between treatment arms (durvalumab or placebo) was not permitted. However, after discontinuation from study treatment, patients from both arms of PACIFIC could switch to subsequent anticancer therapy, including durvalumab and other immunotherapies, which is known to influence standard intention-to-treat analysis of OS, potentially underestimating the effect of an experimental drug. Moreover, the introduction of immunotherapies has demonstrated marked improvements in the postprogression, metastatic non-small cell lung cancer setting.ObjectiveTo examine the influence of subsequent immunotherapy on OS in the PACIFIC trial.MethodsBoth a Rank Preserving Structural Failure Time Model (RPSFTM) and modified 2-stage method were used. RPSFTM assumes that a patient's survival time with no immunotherapy (counterfactual survival time) is equal to the observed time influenced by immunotherapy, multiplied by an acceleration factor, plus the time not influenced. The modified 2-stage method estimates the effect of immunotherapy by comparing postsubsequent-treatment-initiation survival times between patients with and without subsequent immunotherapy. In both models, OS was adjusted to reflect a hypothetical scenario in which no patients received subsequent immunotherapy. RPSFTM was also used for scenarios in which subsequent immunotherapy was received by increasing proportions of placebo patients but none of the durvalumab patients.ResultsIn the intention-to-treat analysis (3-year follow-up), durvalumab improved OS versus placebo (stratified hazard ratio = 0.69; 95% CI, 0.55-0.86). Overall, 10% and 27% of durvalumab and placebo patients, respectively, received subsequent immunotherapy. With subsequent immunotherapy removed from both arms, estimated hazard ratio was 0.66 (95% CI, 0.53-0.84) with RPSFTM and 0.68 (95% CI, 0.54-0.85) with the modified 2-stage method. With subsequent immunotherapy removed from the durvalumab arm only (RPSFTM), estimated hazard ratio increased as the proportion of placebo patients receiving subsequent immunotherapy increased, up to 0.75 (95% CI, 0.60-0.94) maximum (assuming all placebo patients with subsequent treatment received immunotherapy).ConclusionsResults were consistent with the intention-to-treat analysis, supporting the conclusion that durvalumab after chemoradiotherapy provides substantial OS benefit in patients with Stage III, unresectable non-small cell lung cancer. ClinicalTrials.gov identifier: NCT02125461 (Curr Ther Res Clin Exp. 2021; 82:XXX-XXX).

Project description:BackgroundTNM staging alone does not accurately predict outcome in colon cancer (CC) patients who may be eligible for adjuvant chemotherapy. It is unknown to what extent the molecular markers microsatellite instability (MSI) and mutations in BRAF or KRAS improve prognostic estimation in multivariable models that include detailed clinicopathological annotation.Patients and methodsAfter imputation of missing at random data, a subset of patients accrued in phase 3 trials with adjuvant chemotherapy (n = 3016)-N0147 (NCT00079274) and PETACC3 (NCT00026273)-was aggregated to construct multivariable Cox models for 5-year overall survival that were subsequently validated internally in the remaining clinical trial samples (n = 1499), and also externally in different population cohorts of chemotherapy-treated (n = 949) or -untreated (n = 1080) CC patients, and an additional series without treatment annotation (n = 782).ResultsTNM staging, MSI and BRAFV600E mutation status remained independent prognostic factors in multivariable models across clinical trials cohorts and observational studies. Concordance indices increased from 0.61-0.68 in the TNM alone model to 0.63-0.71 in models with added molecular markers, 0.65-0.73 with clinicopathological features and 0.66-0.74 with all covariates. In validation cohorts with complete annotation, the integrated time-dependent AUC rose from 0.64 for the TNM alone model to 0.67 for models that included clinicopathological features, with or without molecular markers. In patient cohorts that received adjuvant chemotherapy, the relative proportion of variance explained (R2) by TNM, clinicopathological features and molecular markers was on an average 65%, 25% and 10%, respectively.ConclusionsIncorporation of MSI, BRAFV600E and KRAS mutation status to overall survival models with TNM staging improves the ability to precisely prognosticate in stage II and III CC patients, but only modestly increases prediction accuracy in multivariable models that include clinicopathological features, particularly in chemotherapy-treated patients.

Project description:BackgroundWe evaluated the impact of thoracic radiation in patients with non-small cell lung cancer (NSCLC), considering the depletion of total lymphocytes, use or not of chemotherapy, and radiation doses in healthy lung tissue.MethodsPatients with stage III NSCLC, ECOG 0 to 2, receiving radiotherapy with or without chemotherapy were prospectively evaluated. All patients should be treated with three-dimensional radiotherapy and received biologically effective doses (BED10α/β 10) of 48 to 80 Gy. Peripheral blood lymphocyte total counts were measured at the start of radiotherapy and at 2, 6 and 12 months after radiotherapy. Along with lymphocytes, PTV and doses of 5 Gy and 20 Gy in healthy lung tissue were also evaluated as potential factors influencing overall survival (OS) and progression-free survival (PFS).ResultsA total of 46 patients were prospectively evaluated from April 2016 to August 2019, with a median follow-up of 13 months (interquartile range, 1-39 months). The median of OS of all cohort was 22,8 months (IC 95% 17,6-28,1) and the median PFS was 19,5 months (IC 95%: 14,7-24,2). Most patients received concurrent or neoadjuvant chemotherapy (43; 93.4%). No patient received adjuvant immunotherapy. The lower the lymphocyte loss at 6 months after radiotherapy (every 100 lymphocytes/mcL), the greater the chance of PFS (HR, 0.44; 95%CI, 0.25-0.77; P = 0.004) and OS (HR, 0.83; 95%CI, 0.70-0.98; P = 0.025; P = 0.025). BED was a protective factor for both PFS (HR, 0.52; 95%CI 0.33-0.83; P = 0.0006) and OS (HR, 0.73; 95%CI 0.54-0.97; P = 0.029).ConclusionsOur results suggest that lymphocyte depletion after radiotherapy reduces tumor control and survival in patients with stage III lung cancer. Radiation doses equal or higher than 60 Gy (BED10 72 Gy) improve PFS and OS, but they negatively affect lymphocyte counts for months, which reduces survival and the potential of immunotherapy.Key pointsSIGNIFICANT FINDINGS OF THE STUDY: Thoracic irradiation for locally advanced lung cancer depletes T lymphocytes for months. Patients whose lymphocyte loss is lower have better overall survival and progression-free survival.What this study addsIt is necessary to protect the lymphocyte population, as well as other organs at risk. New forms of irradiation for large fields are needed. Furthermore, could immunotherapy before chemo-radiotherapy, with a greater number of lymphocytes, bring an even better result?

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A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.

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A Validated Prediction Model for Overall Survival From Stage III Non-Small Cell Lung Cancer: Toward Survival Prediction for Individual Patients.

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