Jay P Bae1, Ran Duan2, Haoda Fu2, Byron J Hoogwerf2. 1. Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana. Electronic address: bae_jay@lilly.com. 2. Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana.
Abstract
PURPOSE: A trade-off exists in most diabetes therapies between the benefits of good glycemic control and the morbidity of hypoglycemia. Balancing these factors to achieve desired outcomes is a key consideration for personalized diabetes therapy. Hypoglycemia at night (nocturnal hypoglycemia [NH]) is a common but often under-reported problem in insulin-treated patients with type 2 diabetes. To better understand the risk for NH, we pooled data from multiple clinical trials of insulin treatment and specifically examined NH risk factors in relation to glycemic goals. METHODS: Of 53 randomized trials involving insulin treatment, 18 trials that collected NH data were included. Risk factors associated with NH were identified by using gradient-boosting methods. A proportional hazards model was used to quantify the hazard ratio (HR) for risk factors. By modeling with individual patient data, a patient-level NH risk score distribution was created. Finally, results of the model were used to quantify an adjustment to the glycemic goal that would fully offset each risk factor, all other factors being equal. FINDINGS: Data pooling resulted in the inclusion of 7341 patients with type 2 diabetes from 18 randomized clinical trials. In the mean 6-month treatment period, 43% of patients experienced at least 1 episode of NH (mean [SD], 1.1 [1.5] events/month). Reduction of glycosylated hemoglobin (HbA1c) levels during the trial was a risk factor for NH (HR, 1.40 [95% CI, 1.38-1.43] per -1% of HbA1c). Higher baseline HbA1c level was a protective factor against NH (HR, 0.76 [95% CI, 0.74-0.77] per +1% of HbA1c); and the adjustment to HbA1c goal required to offset 1% higher baseline HbA1c was -0.825%. Patient characteristics for risk of NH included older age (HR, 1.02 [95% CI, 1.01-1.02]) per 1-year increase), female sex (HR, 1.18 [95% CI, 1.15-1.22]), black or African-American race (HR, 1.41 [95% CI, 1.33-1.50] vs white race), longer diabetes duration (HR, 1.02 [95% CI, 1.01-1.02] per 1-year increase), diabetic nephropathy (HR, 1.40 [95% CI, 1.27-1.54]), and concomitant sulfonylurea use (HR, 1.10 [95% CI, 1.05-1.15]). Asian race was associated with a lower risk of NH (HR, 0.50 [95% CI, 0.48-0.53] vs white race); this finding could be offset with a 2.03% adjustment to the HbA1c goal. IMPLICATIONS: Data on NH are scarce. By pooling multiple clinical trials, this study was able to evaluate patient-level data. A quantitative understanding of the trade-off between individual risk factors for NH and glycemic reduction may help clinicians to personalize patients' glycemic goals, while effectively managing NH risk. Limitations of the study include that patients were selected through inclusion/exclusion criteria and that patient compliance may be better in a trial setting. Validating the findings in the real world will be helpful.
PURPOSE: A trade-off exists in most diabetes therapies between the benefits of good glycemic control and the morbidity of hypoglycemia. Balancing these factors to achieve desired outcomes is a key consideration for personalized diabetes therapy. Hypoglycemia at night (nocturnal hypoglycemia [NH]) is a common but often under-reported problem in insulin-treated patients with type 2 diabetes. To better understand the risk for NH, we pooled data from multiple clinical trials of insulin treatment and specifically examined NH risk factors in relation to glycemic goals. METHODS: Of 53 randomized trials involving insulin treatment, 18 trials that collected NH data were included. Risk factors associated with NH were identified by using gradient-boosting methods. A proportional hazards model was used to quantify the hazard ratio (HR) for risk factors. By modeling with individual patient data, a patient-level NH risk score distribution was created. Finally, results of the model were used to quantify an adjustment to the glycemic goal that would fully offset each risk factor, all other factors being equal. FINDINGS: Data pooling resulted in the inclusion of 7341 patients with type 2 diabetes from 18 randomized clinical trials. In the mean 6-month treatment period, 43% of patients experienced at least 1 episode of NH (mean [SD], 1.1 [1.5] events/month). Reduction of glycosylated hemoglobin (HbA1c) levels during the trial was a risk factor for NH (HR, 1.40 [95% CI, 1.38-1.43] per -1% of HbA1c). Higher baseline HbA1c level was a protective factor against NH (HR, 0.76 [95% CI, 0.74-0.77] per +1% of HbA1c); and the adjustment to HbA1c goal required to offset 1% higher baseline HbA1c was -0.825%. Patient characteristics for risk of NH included older age (HR, 1.02 [95% CI, 1.01-1.02]) per 1-year increase), female sex (HR, 1.18 [95% CI, 1.15-1.22]), black or African-American race (HR, 1.41 [95% CI, 1.33-1.50] vs white race), longer diabetes duration (HR, 1.02 [95% CI, 1.01-1.02] per 1-year increase), diabetic nephropathy (HR, 1.40 [95% CI, 1.27-1.54]), and concomitant sulfonylurea use (HR, 1.10 [95% CI, 1.05-1.15]). Asian race was associated with a lower risk of NH (HR, 0.50 [95% CI, 0.48-0.53] vs white race); this finding could be offset with a 2.03% adjustment to the HbA1c goal. IMPLICATIONS: Data on NH are scarce. By pooling multiple clinical trials, this study was able to evaluate patient-level data. A quantitative understanding of the trade-off between individual risk factors for NH and glycemic reduction may help clinicians to personalize patients' glycemic goals, while effectively managing NH risk. Limitations of the study include that patients were selected through inclusion/exclusion criteria and that patient compliance may be better in a trial setting. Validating the findings in the real world will be helpful.