1.Who succeeds in insulin deintensification? Real-world predictors and modifiable factors from primary care
Yee Theng Chong ; Mohammad Ashwad Muhd Zin ; Anisha K Nijar ; Nur Syellawathy Ahmad ; Mohd Khairi Mohd Noor ; Noorhazliza Abdul Patah ; Erleena Nur Hassan ; Izwan Effendy Ismai ; Najwa Aziz ; Min Chiee Leon ; Hui Ting Ng ; Khairatun Hisan Mohd Napiah ; Manothini A/P Perumal ; Shih Ling Selene Ng Shih Ling ; Ming Hui Liew ; Cha Chee Chong
Journal of the ASEAN Federation of Endocrine Societies 2026;41(S1):4-
Introduction:
Insulin therapy is essential in the management of type 2 diabetes mellitus (T2DM), but is often associated with treatment
burden, hypoglycemia, and potential overtreatment. Insulin deintensification is increasingly recommended for
appropriately selected patients; however, there is limited real-world evidence to guide patient selection and to identify
modifiable factors that influence successful insulin deintensification. This study aimed to identify clinical predictors,
including modifiable factors, associated with successful insulin deintensification in a primary care setting.
Methodology:
A multicentre retrospective observational study was conducted across seven government primary care clinics in the Petaling
District. Adult patients with T2DM undergoing insulin deintensification were included. Successful insulin deintensification
was defined as maintenance or improvement of hemoglobin A1c following insulin discontinuation, dose reduction, or
reduction in injection frequency. Paired outcomes were analyzed using the Wilcoxon signed-rank test. Between-group
comparisons were performed using the Mann–Whitney U test and Chi-square or Fisher’s exact test. Multivariable logistic
regression was used to identify independent predictors of successful insulin deintensification.
Results:
A total of 261 patients were included. Glycemic control remained stable following insulin deintensification (p = 0.334).
Significant reductions in body weight (−0.41 kg, p = 0.012) and total daily insulin dose (23.1% reduction, p <0.001) were
observed. Univariate analysis did not demonstrate significant differences between groups. However, multivariable logistic
regression identified SGLT-2 inhibitor use (aOR 3.23, 95% CI 1.28–8.18, p = 0.013) and regular SMBG (aOR 2.00, 95% CI
1.05–3.81, p = 0.035) as independent predictors of successful insulin deintensification.
Conclusion
Insulin deintensification can be successfully implemented without compromising glycemic control. Identified predictors,
including modifiable factors such as SGLT-2 inhibitor use and SMBG, provide clinically actionable insights to guide patient
selection and treatment optimization. These findings challenge the traditional reluctance toward insulin deintensification
and support a more evidence-based and individualized approach in routine clinical practice.
Primary Health Care
;
Insulins

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