Search

Acute oncology services (AOS) provide rapid review and expedited pathways for referral to specialist care for cancer patients. Blood tests may support AOS in providing estimates of prognosis. We aimed to develop and validate a prognostic model of 30-day mortality based on routine blood markers to inform an AOS decision to actively treat or palliate patients. Using clinical data from 752 AOS referrals, multivariable logistic regression analysis was conducted to develop a 30-day mortality prognostic model. Internal validation and then internal–external cross-validation were used to examine overfitting and generalizability of the model's predictive performance. Urea, alkaline phosphatase, albumin and neutrophils were the strongest predictors of outcome. The model separated patients into distinct prognostic groups from the cross-validation (C Statistic: 0.70; 95% CI: 0.64–0.76). Admission year was included as a predictor in the model to improve the model calibration. The developed prediction model was able to classify patients into distinct prognostic risk groups, which is clinically useful for delivering an evidence-based AOS. Collation of data from other AOS centers would allow for the development of a more generalizable prognostic model. [ABSTRACT FROM AUTHOR]

Clinical prediction models provide individualized outcome predictions to inform patient counseling and clinical decision making. External validation is the process of examining a prediction model's performance in data independent to that used for model development. Current external validation studies often suffer from small sample sizes, and subsequently imprecise estimates of a model's predictive performance. To address this, we propose how to determine the minimum sample size needed for external validation of a clinical prediction model with a continuous outcome. Four criteria are proposed, that target precise estimates of (i) R2 (the proportion of variance explained), (ii) calibration‐in‐the‐large (agreement between predicted and observed outcome values on average), (iii) calibration slope (agreement between predicted and observed values across the range of predicted values), and (iv) the variance of observed outcome values. Closed‐form sample size solutions are derived for each criterion, which require the user to specify anticipated values of the model's performance (in particular R2) and the outcome variance in the external validation dataset. A sensible starting point is to base values on those for the model development study, as obtained from the publication or study authors. The largest sample size required to meet all four criteria is the recommended minimum sample size needed in the external validation dataset. The calculations can also be applied to estimate expected precision when an existing dataset with a fixed sample size is available, to help gauge if it is adequate. We illustrate the proposed methods on a case‐study predicting fat‐free mass in children. [ABSTRACT FROM AUTHOR]

Introduction: Childhood adiposity markers can be standardised for height in the form of indices (marker/height p ) to make meaningful comparisons of adiposity patterns within and between individuals of differing heights. The optimal value of p has been shown to differ by birth year, sex, age, and ethnicity. We investigated whether height powers for childhood weight and fat mass (FM) differed by birth year, sex, or age over the period before and during the child obesity epidemic in Copenhagen., Setting/methods: Population-based cross-sectional study of 391,801 schoolchildren aged 7 years, 10 years and 13 years, born between 1930 and 1996, from the Copenhagen School Health Records Register. Sex- and age-specific estimates of the height powers for weight and FM were obtained using log-log regression, stratified by a decade of birth., Results: For weight, amongst children born 1930-39, optimal height powers at 7 years were 2.20 (95% CI: 2.19-2.22) for boys and 2.28 (95% CI: 2.26-2.30) for girls. These increased with birth year to 2.82 (95% CI: 2.76-2.87) and 2.92 (95% CI: 2.87-2.97) for boys and girls born in 1990-96, respectively. For FM, amongst those born 1930-39, powers at 7 years were 2.46 (95% CI: 2.42-2.51) and 2.58 (95% CI: 2.53-2.63) for boys and girls, respectively, and increased with birth year reaching 3.89 (95% CI: 3.75-4.02) and 3.93 (95% CI: 3.80-4.06) for boys and girls born 1990-96, respectively. Powers within birth cohort groups for weight and FM were higher at 10 years than at 7 years, though similar increases across groups were observed at both ages. At 13 years, height powers for weight and FM initially increased with the birth year before declining from the 1970s/80s., Conclusion: Due to increases in the standard deviation of weight and FM during the obesity epidemic, optimal height powers needed to standardise childhood weight and FM varied by birth year, sex, and age. Adiposity indices using a uniform height power mean different things for different birth cohort groups, sexes, and ages thus should be interpreted with caution. Alternative methods to account for height in epidemiological analyses are needed., (© 2024. The Author(s).)

Objective: National body fatness (BF) data for English South Asian and Black children use BMI, which provides inaccurate ethnic comparisons. BF levels and time trends in the English National Child Measurement Programme (NCMP) between 2007 and 2013 were assessed by using ethnic-specific adjusted BMI (aBMI) for South Asian and Black children., Methods: Analyses were based on 3,195,323 children aged 4 to 5 years and 2,962,673 children aged 10 to 11 years. aBMI values for South Asian and Black children (relating to BF as in White children) were derived independently. Mean aBMI levels and 5-year aBMI changes were obtained by using linear regression., Results: In the 2007-2008 NCMP, mean aBMIs in 10- to 11-year-old children (boys, girls) were higher in South Asian children (20.1, 19.9 kg/m 2 ) and Black girls, but not in Black boys (18.4, 19.2 kg/m 2 ) when compared with White children (18.6, 19.0 kg/m 2 ; all P < 0.001). Mean 5-year changes (boys, girls) were higher in South Asian children (0.16, 0.32 kg/m 2 per 5 y; both P < 0.001) and Black boys but not girls (0.13, 0.15 kg/m 2 per 5 y; P = 0.01, P = 0.41) compared with White children (0.02, 0.11 kg/m 2 per 5 y). Ethnic differences at 4 to 5 years were similar. Unadjusted BMI showed similar 5-year changes but different mean BMI patterns., Conclusions: BF levels were higher in South Asian children than in other groups in 2007 and diverged from those in White children until 2013, a pattern not apparent from unadjusted BMI data., (© 2017 The Authors. Obesity published by Wiley Periodicals, Inc. on behalf of The Obesity Society (TOS).)