Errors in Abstract, Statistical Analysis, and Results

In the Original Investigation titled “Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark,”¹ published online October 23, 2019, there were errors in the Abstract, Statistical Analysis, and Results. In the Abstract, the following sentence should have been removed: “For example, stress disorders among unmarried men older than 30 years were important factors for suicide risk in the presence of depression (risk, 0.54).”

In the second paragraph of the Statistical Analysis, the number of predictor variables given as 2554 should have been 2564. In the first and second paragraphs of the Random Forest section of the Results, predictors enumerated as “Seventeen” and “Nineteen” should have been “Eighteen” and “Twenty-one,” respectively.

In the second paragraph of the Results in CART Remodeling, the first 2 sentences were given as “Among men, the highest risk for suicide was found among those younger than 30 years who were diagnosed with schizophrenia in the past 2 years but without recorded prescriptions for antidepressants, antipsychotics, medications for addictions (eg, methadone), or hypnotics or sedatives (n = 26; risk, 0.58). Similarly, unmarried men older than 30 years who had been diagnosed with a stress disorder in the prior 4 years but did not have a recorded prescription for these medications had a risk of 0.54 (n = 37).” The sentences should have appeared as “Among men, the highest risk for suicide was found among those not being treated by pharmacotherapy (eg, antidepressants, antipsychotics, or anxiolytics) and with a prior suicide attempt in the prior 4 years, and being in the second income quartile (n = 18; risk, 1.0). Similarly, men who received a prior diagnosis of poisoning by adverse effects or underdosing of drugs but did not have a coded prescription for antidepressants, antipsychotics, medications for addictions (eg, methadone), or hypnotics/sedatives in the prior 4 years had a risk of 0.42 (n = 251).” This article was corrected online.