Several of these non-invasive models exhibited good calibration and discrimination within both external validation populations and are therefore potentially suitable candidates for the facilitation of risk stratification in population-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained.
Colorectal cancer (CRC) risk prediction models could be used to risk-stratify the population to provide individually tailored screening provision. Using participants from the UK Biobank prospective cohort study, we evaluated whether the addition of a genetic risk score (GRS) could improve the performance of two previously validated models. Inclusion of the GRS did not appreciably improve discrimination of either model, and led to substantial miscalibration. Following recalibration the discrimination did not change, but good calibration for models incorporating the GRS was recovered. Comparing predictions between models with and without the GRS, 5% of participants or fewer changed their absolute risk by ±0.3% or more in either model. In summary, addition of a GRS did not meaningfully improve the performance of validated CRC-risk prediction models. At present, provision of genetic information is not useful for risk stratification for CRC.
BackgroundFew published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction.MethodsWe built two models, for ER+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51% postmenopausal at recruitment) from the European Prospective Investigation into Cancer and Nutrition cohort. Discrimination (C-statistic) and calibration (the agreement between predicted and observed tumor risks) were assessed both internally and externally in 82,319 postmenopausal women from the Women’s Health Initiative study. We performed decision curve analysis to compare ModelER+ and the Gail model (ModelGail) regarding their applicability in risk assessment for chemoprevention.ResultsParity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for ModelER+ and 0.59 for ModelER-. External validation reduced the C-statistic of ModelER+ (0.59) and ModelGail (0.57). In external evaluation of calibration, ModelER+ outperformed the ModelGail: the former led to a 9% overestimation of the risk of ER+ tumors, while the latter yielded a 22% underestimation of the overall BC risk. Compared with the treat-all strategy, ModelER+ produced equal or higher net benefits irrespective of the benefit-to-harm ratio of chemoprevention, while ModelGail did not produce higher net benefits unless the benefit-to-harm ratio was below 50. The clinical applicability, i.e. the area defined by the net benefit curve and the treat-all and treat-none strategies, was 12.7 × 10− 6 for ModelER+ and 3.0 × 10− 6 for ModelGail.ConclusionsModeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.
Nesiritide is a recombinant formulation of B-type natriuretic peptide (BNP). Preliminary experience in the adult population has shown nesiritide to be an effective agent in the treatment of decompensated congestive heart failure (CHF) in adults. Given its physiological effects, it may be an effective agent in other clinical scenarios. We report the use of nesiritide in two infants during extracorporeal membrane oxygenation (ECMO). In one patient, nesiritide in doses up to 0.09 microg.kg(-1).min(-1) were used to control mean arterial pressure while in the other patient, doses of 0.01-0.03 microg.kg(-1).min(-1) were used to augment urine output. The potential applications of nesiritide and dosing regimens for this agent in the ECMO population are discussed.
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