Premium
Using survival modelling as a composite measure of outcome to demonstrate insulin pump therapy effectiveness in type 1 diabetes
Author(s) -
Yamanouchi Liana,
Leong Wen Bun,
Lloyd Joanne,
Smith Angela,
Davies Peter,
Basu Ansu
Publication year - 2020
Publication title -
practical diabetes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.205
H-Index - 24
eISSN - 2047-2900
pISSN - 2047-2897
DOI - 10.1002/pdi.2264
Subject(s) - medicine , observational study , proportional hazards model , type 2 diabetes , diabetes mellitus , glycated hemoglobin , insulin , survival analysis , linear regression , insulin pump , cohort , covariate , regression analysis , type 1 diabetes , endocrinology , statistics , mathematics
Abstract Glycated haemoglobin (HbA 1c ) is a time‐series measure subject to variability; quantifying the difference between the first and last readings over a defined period may have little value in measuring success in service evaluation models. Identifying a composite measure for outcome would be an invaluable tool for service providers. We demonstrate the efficacy of survival modelling as a composite measure of outcome. This was a retrospective observational cohort analysis of patients with type 1 diabetes on insulin pump therapy. From these data, a service evaluation project was undertaken. Survival (time‐to‐event) analysis was undertaken for two HbA 1c values – 58 and 64mmol/mol (7.5% and 8.0%); analyses were based on time taken to reach the index HbA 1c value (58 or 64mmol/mol) for the first time from start of pump therapy. A total of 113 patients were treated with the insulin pump. The median time to reach an HbA 1c of 58 and 64mmol/mol was 25 and 13.9 months, respectively. Cox regression using gender, HbA 1c , weight and age prior to pump therapy as factor variables identified HbA 1c as the only predictor that significantly influenced the time‐to‐event (HR 0.94, p=0.001 for HbA 1c 58mmol/mol, and HR 0.97, p=0.008 for HbA 1c 64mmol/mol). Survival modelling appears to be a robust statistical tool to evaluate performance. Furthermore, adjusting for covariates identifies factors that may influence outcome. Pump therapy is considered a high cost area by commissioners, therefore having auditable outcome measures would be useful to inform authorities on the effectiveness of the service. Copyright © 2020 John Wiley & Sons.