Clinical Prediction Models

External validation of the fatty liver index and lipid accumulation product indices, using 1H-magnetic resonance spectroscopy, to identify hepatic steatosis in healthy controls and obese, insulin-resistant individuals

“…As FLI can also be interpreted as a predictive probability for hepatic steatosis, we assessed how wellcalibrated FLI was in our patient cohort using a calibration plot (27). To do so, we grouped patients into deciles based on measured FLI and within each decile calculated the proportion of patients with hepatic steatosis.…”

A Clinical Prediction Model for Time in Therapeutic Range While on Warfarin in Newly Diagnosed Atrial Fibrillation

“…Missing vital sign and laboratory data are not missing at random-missing implies healthier-thus, usual imputation techniques were not applied. 37,38 The imputation method was intentionally chosen to be a conservative approach, more likely to attenuate effect estimates. Other data analysis tactics could have been used; however, we emphasize that the final prediction model only endorses data patterns independently observed in both the development and validation sets, which lend credibility to their veracity.…”

“…37,38 Linear regression modeling was used and a forward stepwise variable selection algorithm applied in order to identify the strongest independent predictors of continuous TTR. 38,39 All models generated during the variable selection process were reviewed closely for collinearity and adjustments made as needed.…”

“…37,38 Linear regression modeling was used and a forward stepwise variable selection algorithm applied in order to identify the strongest independent predictors of continuous TTR. 38,39 All models generated during the variable selection process were reviewed closely for collinearity and adjustments made as needed. As all variables were placed on categorical scales (binary or 6-group variables as described above), the criterion for variable inclusion/exclusion in the development set was an absolute 3% difference in TTR across a variable's levels as opposed to the usual P-value threshold criterion.…”

Re: Predicting successful vaginal birth after Cesarean section using a model based on Cesarean scar features examined using transvaginal sonography

“…There is no plausible mechanism that explains why these variables have such an impact on the probability of success. Furthermore, rather than choosing predictors based on observed significant relations to outcome variables in the same dataset, contemporary methodological guidelines for prediction research state that predictors should be chosen based on preselection 4 , a method that results in higher external validity and less overfitting. Therefore, we would like to emphasize the importance of external validation of these predictors in other data.…”