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51.

Introduction

Malignant pleural mesothelioma (MPM) is an uncommon cancer with a poor prognosis and heterogeneous survival. Surgery for MPM is offered in some specialist centers to highly selected patients. A previously described classification and regression tree (CART) model stratified survival in unselected MPM patients using routinely collected clinical data. This study aimed to examine the performance of this CART model on a highly selected surgical population.

Methods

Data were collected from subjects undergoing cytoreductive surgery for MPM from specialist centers in Hyõgo, Japan, and Sydney, Australia, between 1991 and 2016. The CART model was applied using the combination of clinical variables to stratify subjects into risk groups (1 through 4); survival characteristics were then compared.

Results

Two hundred eighty-nine cases were included (205 from Australia, 84 from Japan). Overall median survival was 34.6 (interquartile range: 17.5–56.1) months; median age was 63.0 (interquartile range: 57.0–67.8) years, and 83.0% (n = 240) were male. There were no clinically meaningful differences between the two cohorts. Survival across the four risk groups was significantly different (p < 0.0001); the model stratified survival well with a Harrell's concordance statistic of 0.62 (95% confidence interval: 0.57–0.66) at 36 months. The group with the longest survival (median, 82.5 months) had: no weight loss, hemoglobin > 153 g/L and serum albumin > 43 g/L at time of referral to the surgical center.

Conclusions

Using routinely available clinical variables, the CART model was able to stratify surgical patients into risk groups with statistically different survival characteristics with fair to good performance. Presence of weight loss, anemia, and low albumin should confer caution when considering surgical therapy for MPM.  相似文献   
52.
locStra is an ‐package for the analysis of regional and global population stratification in whole‐genome sequencing (WGS) studies, where regional stratification refers to the substructure defined by the loci in a particular region on the genome. Population substructure can be assessed based on the genetic covariance matrix, the genomic relationship matrix, and the unweighted/weighted genetic Jaccard similarity matrix. Using a sliding window approach, the regional similarity matrices are compared with the global ones, based on user‐defined window sizes and metrics, for example, the correlation between regional and global eigenvectors. An algorithm for the specification of the window size is provided. As the implementation fully exploits sparse matrix algebra and is written in C++, the analysis is highly efficient. Even on single cores, for realistic study sizes (several thousand subjects, several million rare variants per subject), the runtime for the genome‐wide computation of all regional similarity matrices does typically not exceed one hour, enabling an unprecedented investigation of regional stratification across the entire genome. The package is applied to three WGS studies, illustrating the varying patterns of regional substructure across the genome and its beneficial effects on association testing.  相似文献   
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