1. The strongest predictor of all-cause mortality in men was found to be self-reported health, which can be acquired without a physical examination, whereas the strongest predictor of all-cause mortality in women was a previous cancer diagnosis.
2. The strongest predictors of all-cause mortality were measures of smoking habits when individuals with major diseases or disorders were excluded.
3. A prognostic score developed in this study was accurate in predicting 5-year mortality risk using 13 predictors for men and 11 for women.
Evidence Rating Level: 1 (Excellent)
Study Rundown: Prediction of mortality using prognostic indicators is critical for accurate clinical decision-making. Utilizing data from the UK Biobank health database, this study aimed to investigate predictors of all-cause and cause-specific mortality during a 5-year period, and to create a prediction score for 5-year mortality using only self-reported information. Data from about 500,000 UK Biobank participants on 655 demographics, health, and lifestyle measurements were assessed for sex-specific associations with 5-year all-cause mortality and six cause-specific mortality categories utilizing the Cox proportional hazard model.
The strongest predictor of all-cause mortality in men was found to be self-reported health, which can be obtained without the need for a physical examination, whereas the strongest predictor of all-cause mortality in women was a previous cancer diagnosis. The strongest predictors of all-cause mortality were measures of smoking habits when individuals with major diseases or disorders were excluded. Finally, a prognostic index for 5 year-mortality calibrated for individuals aged 40-70 years was accurate in predicting health risk. This study’s prospective design with high rates of follow-up is a key strength of this analysis. The predictions this study makes must be interpreted with caution when applied across populations, due to similarity of the test cohort.
In-Depth [prospective cohort]: This prospective population-based study aimed to assess various predictors of mortality utilizing data from the UK Biobank database. Data from 498,103 participants aged 37-73 years, from England, Wales, and Scotland who were enrolled in the UK Biobank project from April 2007 to July 2010 were analyzed for sex-specific associations of 655 measurements of health, demographics, and lifestyle with all-cause mortality and six cause specific mortality categories. Variables missing in over 80% of participants were excluded from the analysis.
8,532 individuals (including 39% women) died during a median follow-up of 4.9 years. The strongest predictor or all-cause mortality in men was self-reported health (C-index including age 0.74 [95% CI 0.73-0.75]). The strongest predictor of all-cause mortality in women was to be a previous cancer diagnosis (0.73 [0.72-0.74]). Measures of smoking habits were the strongest predictors of all-cause mortality when individuals with major diseases or disorders were excluded (Charlson comorbidity index >0; n=355,043). A prognostic score based on 13 self-reported predictors for men and 11 for women achieved better performance than the Charlson comorbidity index (p<0.0001 in men and p=0.0007 in women) and good discrimination (0.80 [0.77-0.83] for men and 0.79 [0.76-0.83] for women).
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