ArticleEuropean journal of public health2017
Predicting risk of substantial weight gain in German adults-a multi-center cohort approach.
Article in European journal of public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Limited Weight Impact After Switching From Boosted Protease Inhibitors to Dolutegravir in Persons With Human Immunodeficiency Virus With High Cardiovascular Risk: A Post Hoc Analysis of the 96-Week NEAT-022 Randomized Trial.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Trial
- Weight Gain after Interferon-Free Treatment of Chronic Hepatitis C-Results from the German Hepatitis C-Registry (DHC-R).Biomedicines · 2021Article
- A Multi-Center Competing Risks Model and Its Absolute Risk Calculation Approach.International journal of environmental research and public health · 2019Article
- A Stroke Risk Detection: Improving Hybrid Feature Selection Method.Journal of medical Internet research · 2019Article
- Using metabolite profiling to construct and validate a metabolite risk score for predicting future weight gain.PloS one · 2019Article
Corrections and comments
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Authors and funding
16 authors at 8 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: A risk-targeted prevention strategy may efficiently utilize limited resources available for prevention of overweight and obesity. Likewise, more efficient intervention trials could be designed if selection of subjects was based on risk. The aim of the study was to develop a risk score predicting substantial weight gain among German adults. Methods: We developed the risk score using information on 15 socio-demographic, dietary and lifestyle factors from 32 204 participants of five population-based German cohort studies. Substantial weight gain was defined as gaining ≥10% of weight between baseline and follow-up (>6 years apart). The cases were censored according to the theoretical point in time when the threshold of 10% baseline-based weight gain was crossed assuming linearity of weight gain. Beta coefficients derived from proportional hazards regression were used as weights to compute the risk score as a linear combination of the predictors. Cross-validation was used to evaluate the score's discriminatory accuracy. Results: The cross-validated c index (95% CI) was 0.71 (0.67-0.75). A cutoff value of ≥475 score points yielded a sensitivity of 71% and a specificity of 63%. The corresponding positive and negative predictive values were 10.4% and 97.6%, respectively. Conclusions: The proposed risk score may support healthcare providers in decision making and referral and facilitate an efficient selection of subjects into intervention trials.
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Registered trials
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