Dataset Information

A Nomogram to Predict Recurrence and Survival of High-Risk Patients Undergoing Sublobar Resection for Lung Cancer: An Analysis of a Multicenter Prospective Study (ACOSOG Z4032).

ABSTRACT: Individualized prediction of outcomes may help with therapy decisions for patients with non-small cell lung cancer. We developed a nomogram by analyzing 17 clinical factors and outcomes from a randomized study of sublobar resection for non-small cell lung cancer in high-risk operable patients. The study compared sublobar resection alone with sublobar resection with brachytherapy. There were no differences in primary and secondary outcomes between the study arms, and they were therefore combined for this analysis.The clinical factors of interest (considered as continuous variables) were assessed in a univariate Cox proportional hazards model for significance at the 0.10 level for their impact on overall survival (OS), local recurrence-free survival (LRFS), and any recurrence-free survival (RFS). The final multivariable model was developed using a stepwise model selection.Of 212 patients, 173 had complete data on all 17 risk factors. Median follow-up was 4.94 years (range, 0.04 to 6.22). The 5-year OS, LRFS, and RFS were 58.4%, 53.2%, and 47.4%, respectively. Age, baseline percent diffusing capacity of lung for carbon monoxide, and maximum tumor diameter were significant predictors for OS, LRFS, and RFS in the multivariable model. Nomograms were subsequently developed for predicting 5-year OS, LRFS, and RFS.Age, baseline percent diffusing capacity of lung for carbon monoxide, and maximum tumor diameter significantly predicted outcomes after sublobar resection. Such nomograms may be helpful for treatment planning in early stage non-small cell lung cancer and to guide future studies.

SUBMITTER: Kent MS

PROVIDER: S-EPMC4993046 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Nomogram to Predict Recurrence and Survival of High-Risk Patients Undergoing Sublobar Resection for Lung Cancer: An Analysis of a Multicenter Prospective Study (ACOSOG Z4032).

Kent Michael S MS Mandrekar Sumithra J SJ Landreneau Rodney R Nichols Francis F Foster Nathan R NR DiPetrillo Thomas A TA Meyers Bryan B Heron Dwight E DE Jones David R DR Tan Angelina D AD Starnes Sandra S Putnam Joe B JB Fernando Hiran C HC

The Annals of thoracic surgery 20160419 1

<h4>Background</h4>Individualized prediction of outcomes may help with therapy decisions for patients with non-small cell lung cancer. We developed a nomogram by analyzing 17 clinical factors and outcomes from a randomized study of sublobar resection for non-small cell lung cancer in high-risk operable patients. The study compared sublobar resection alone with sublobar resection with brachytherapy. There were no differences in primary and secondary outcomes between the study arms, and they were ...[more]

PMID: 27101729

Similar Datasets

Project description:Adrenocortical carcinoma (ACC) is a rare but aggressive endocrine tumor, and the prognostic factors associated with long-term outcomes after surgical resection remain poorly defined.To define clinicopathological variables associated with recurrence-free survival (RFS) and overall survival (OS) after curative surgical resection of ACC and to propose nomograms for individual risk prediction.Nomograms to predict RFS and OS after surgical resection of ACC were proposed using a multi-institutional cohort of patients who underwent curative-intent surgery for ACC at 13 major institutions in the United States between March 17, 1994, and December 22, 2014. The dates of our study analysis were April 15, 2015, to May 12, 2015.The discriminative ability and calibration of the nomograms to predict RFS and OS were tested using C statistics, calibration plots, and Kaplan-Meier curves.In total, 148 patients who underwent surgery for ACC were included in the study. The median patient age was 53 years, and 65.5% (97 of 148) of the patients were female. One-third of the patients (35.1% [52 of 148]) had a functional tumor, and the median tumor size was 11.2 cm. Most patients (77.7% [115 of 148]) underwent R0 resection, and 8.8% (13 of 148) of the patients had N1 disease. Using backward stepwise selection of clinically important variables with the Akaike information criterion, the following variables were incorporated in the prediction of RFS: tumor size of at least 12 cm (hazard ratio [HR], 3.00; 95% CI, 1.63-5.70; P <?.001), positive nodal status (HR, 4.78; 95% CI, 1.47-15.50; P =?.01), stage III/IV (HR, 1.80; 95% CI, 0.95-3.39; P =?.07), cortisol-secreting tumor (HR, 2.38; 95% CI, 1.27-4.48; P =?.01), and capsular invasion (HR, 1.96; 95% CI, 1.02-3.74; P =?.04). Factors selected as predicting OS were tumor size of at least 12 cm (HR, 1.78; 95% CI, 1.00-3.17; P =?.05), positive nodal status (HR, 5.89; 95% CI, 2.05-16.87; P =?.001), and R1 margin (HR, 2.83; 95% CI, 1.51-5.30; P =?.001). The discriminative ability and calibration of the nomograms revealed good predictive ability as indicated by the C statistics (0.74 for RFS and 0.70 for OS).Independent predictors of survival and recurrence risk after curative-intent surgery for ACC were selected to create nomograms predicting RFS and OS. The nomograms were able to stratify patients into prognostic groups and performed well on internal validation.

Dataset Information

A Nomogram to Predict Recurrence and Survival of High-Risk Patients Undergoing Sublobar Resection for Lung Cancer: An Analysis of a Multicenter Prospective Study (ACOSOG Z4032).

Publications

A Nomogram to Predict Recurrence and Survival of High-Risk Patients Undergoing Sublobar Resection for Lung Cancer: An Analysis of a Multicenter Prospective Study (ACOSOG Z4032).

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets