Dose volume histogram points (DVHPs) frequently serve as dose constraints in radiotherapy treatment planning. An experiment was designed to investigate the reliability of DVHP inference from clinical data for multiple cohort sizes and complication incidence rates. The experimental background was radiation pneumonitis in non-small cell lung cancer and the DVHP inference method was based on logistic regression. From 102 NSCLC real-life dose distributions and a postulated DVHP model, an ‘ideal’ cohort was generated where the most predictive model was equal to the postulated model. A bootstrap and a Cohort Replication Monte Carlo (CoRepMC) approach were applied to create 1000 equally sized populations each. The cohorts were then analyzed to establish inference frequency distributions. This was applied to nine scenarios for cohort sizes of 102 (1), 500 (2) to 2000 (3) patients (by sampling with replacement) and three postulated DVHP models. The Bootstrap was repeated for a ‘no...
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Abstract Kenaf is a multipurpose crop, but a lack of genetic information hinders genetic and molecular research. In this study, we aimed t...
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Lichtenstein intervention is currently the classic model of the regulated treatment of inguinal hernias by direct local approach. This “tens...
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Abstract Despite the recent promising results of clinical trials using human pluripotent stem cell (hPSC)-based cell therapies for age-rel...
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Abstract Deducing the scapular positions of extinct tetrapod skeletons remains difficult, because the scapulae and rib cage are connected ...
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