sFlt-1/PlGF ratio for prediction of preeclampsia in clinical routine: A pragmatic real-world analysis of healthcare resource utilisation.

BACKGROUND: We investigated the impact of the soluble fms-like tyrosine kinase 1 (sFlt-1)/placental growth factor (PlGF) ratio to predict short-term risk of preeclampsia on clinical utility and healthcare resource utilisation using real-world data (RWD), and compared findings with health economic modelling from previous studies. METHODS AND FINDINGS: This retrospective analysis compared data from the German population of a multicentre clinical study (PROGNOSIS, n = 203; sFlt-1/PlGF ratio blinded and unavailable for decision-making) with RWD from University Hospital Leipzig, Germany (n = 281; sFlt-1/PlGF ratio used to guide clinical decision-making). A subgroup of the RWD cohort with the same inclusion criteria as the PROGNOSIS trial (RWD prediction only, n = 99) was also included. sFlt-1/PlGF ratio was measured using fully automated Elecsys® sFlt-1 and PlGF immunoassays (cobas e analyser; Roche Diagnostics). A similar proportion of women in the RWD and PROGNOSIS cohorts experienced preeclampsia (14.95% vs. 13.79%; p = 0.7938); a smaller proportion of women in the RWD prediction only cohort experienced preeclampsia versus PROGNOSIS (6.06%; p = 0.0526). In women with preeclampsia, median gestational age at delivery (weeks) was comparable in the RWD and PROGNOSIS cohorts (34.0 vs. 34.3, p = 0.5895), but significantly reduced in the RWD prediction only cohort versus PROGNOSIS (27.1, p = 0.0038). sFlt-1/PlGF ratio at baseline visit was not statistically significantly different for the RWD and PROGNOSIS cohorts, irrespective of preeclampsia outcome. Hospitalisations for confirmed preeclampsia were significantly shorter in the RWD cohort versus PROGNOSIS (median 1 vs. 4 days, p = 0.0093); there was no significant difference between RWD prediction only and PROGNOSIS (3 days, p = 0.9638). All-cause hospitalisations were significantly shorter in the RWD (median 1 day; p<0.0001) and RWD prediction only (1 day; p<0.0001) cohorts versus PROGNOSIS (3 days). CONCLUSIONS: This study supports the findings of previous studies, showing that routine clinical use of the sFlt-1/PlGF ratio may result in shorter duration of hospitalisations, with potential economic benefits.

A Bayesian scoring rule on clustered event data for familial risk assessment - An example from colorectal cancer screening.

Colorectal cancer screening is well established. The identification of high risk populations is the key to implement effective risk-adjusted screening. Good statistical approaches for risk prediction do not exist. The family's colorectal cancer history is used for identification of high risk families and usually assessed by a questionnaire. This paper introduces a prediction algorithm to designate a family for colorectal cancer risk and discusses its statistical properties. The new algorithm uses Bayesian reasoning and a detailed family history illustrated by a pedigree and a Lexis diagram. The algorithm is able to integrate different hereditary mechanisms that define complex latent class or random factor structures. They are generic and do not reflect specific genetic models. This is comparable to strategies in complex segregation analysis. Furthermore, the algorithm can integrate different statistical penetrance models for right censored event data. Computational challenges related to the handling of the likelihood are discussed. Simulation studies assess the predictive quality of the new algorithm in terms of ROC curves and corresponding AUCs. The algorithm is applied to data of a recent study on familial colorectal cancer risk. Its predictive performance is compared to that of a questionnaire currently used in screening for familial colorectal cancer. The results of the proposed algorithm are robust against different inheritance models. Using the simplest hereditary mechanism, the simulation study provides evidence that the algorithm improves detection of families with high cancer risk in comparison to the currently used questionnaire. The applicability of the algorithm goes beyond the field of colorectal cancer.