Validating the UK prospective diabetes study outcome model 2 using data of 94,946 Israeli patients with type 2 diabetes

Xiaohui Zhuo, Cheli Melzer Cohen, Jieling Chen, Gabriel Chodick, Adnan Alsumali, John Cook

Research output: Contribution to journalArticlepeer-review


Aims: To externally validate the United Kingdom Prospective Diabetes Study (UKPDS) Outcome Model 2 (OM2) in contemporary Israeli patient populations. Methods: De-identified patient data on demographics, time-varying risk factors, and clinical events of newly diagnosed type 2 diabetes patients were extracted from the Maccabi Healthcare Services (MHS) diabetes registry over years 2000–2013. Depending on the baseline risk, patients were categorized into low-risk and intermediate-risk groups. In addition to assessing discriminatory performance, the predicted and observed 15-year cumulative incidences of diabetes complications and death were compared among all patients and for the two risk-groups. Results: The discriminatory capability of OM2 was moderate to good, C-statistic ranging 0.71–0.95. The model overpredicted the risk for MI, blindness and death (Predicted/Observed events (P/O: 1.32–2.31)), and underpredicted the risk of IHD (P/O: 0.5). In patients with a low baseline risk, overpredictions were even more pronounced. OM2 performed well in predicting renal failure and ulcer risk in patients with a low risk but predicted well the risk of death, stroke, CHF, and amputation in patients with an intermediate risk. Conclusion: OM2 demonstrated good to moderate discrimination capability for predicting diabetes complications and mortality risks in Israeli diabetes population. The prediction performance differed between patients with different baseline risks.

Original languageEnglish
Article number108086
JournalJournal of Diabetes and its Complications
Issue number1
StatePublished - Jan 2022


  • Diabetes complications
  • External validation
  • Prediction
  • Risk equations
  • Type 2 diabetes

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Endocrinology


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