RESUMO
BACKGROUND/OBJECTIVES: Pragmatic trials are increasingly used to study the implementation of weight loss interventions in real-world settings. This study compared researcher-measured body weights versus electronic medical record (EMR)-derived body weights from a pragmatic trial conducted in an underserved patient population. SUBJECTS/METHODS: The PROPEL trial randomly allocated 18 clinics to usual care (UC) or to an intensive lifestyle intervention (ILI) designed to promote weight loss. Weight was measured by trained technicians at baseline and at 6, 12, 18, and 24 months. A total of 11 clinics (6 UC/5 ILI) with 577 enrolled patients also provided EMR data (n = 561), which included available body weights over the period of the trial. RESULTS: The total number of assessments were 2638 and 2048 for the researcher-measured and EMR-derived body weight values, respectively. The correlation between researcher-measured and EMR-derived body weights was 0.988 (n = 1 939; p < 0.0001). The mean difference between the EMR and researcher weights (EMR-researcher) was 0.63 (2.65 SD) kg, and a Bland-Altman graph showed good agreement between the two data collection methods; the upper and lower boundaries of the 95% limits of agreement are -4.65 kg and +5.91 kg, and 71 (3.7%) of the values were outside the limits of agreement. However, at 6 months, percent weight loss in the ILI compared to the UC group was 7.3% using researcher-measured data versus 5.5% using EMR-derived data. At 24 months, the weight loss maintenance was 4.6% using the technician-measured data versus 3.5% using EMR-derived data. CONCLUSION: At the group level, body weight data derived from researcher assessments and an EMR showed good agreement; however, the weight loss difference between ILI and UC was blunted when using EMR data. This suggests that weight loss studies that rely on EMR data may require larger sample sizes to detect significant effects. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov number NCT02561221.
Assuntos
Registros Eletrônicos de Saúde , Obesidade , Peso Corporal , Humanos , Estilo de Vida , Obesidade/diagnóstico , Obesidade/terapia , Redução de PesoRESUMO
INTRODUCTION: Breast cancer is a heterogeneous disease, consisting of multiple molecular subtypes. Obesity has been associated with an increased risk for postmenopausal breast cancer, but few studies have examined breast cancer subtypes separately. Obesity is often complicated by type 2 diabetes, but the possible association of diabetes with specific breast cancer subtypes remains poorly understood. METHODS: In this retrospective case-control study, Louisiana Tumor Registry records of primary invasive breast cancer diagnosed in 2010-2015 were linked to electronic health records in the Louisiana Public Health Institute's Research Action for Health Network. Controls were selected from Research Action for Health Network and matched to cases by age and race. Conditional logistic regression was used to identify metabolic risk factors. Data analysis was conducted in 2020â2021. RESULTS: There was a significant association between diabetes and breast cancer for Luminal A, Triple-Negative Breast Cancer, and human epidermal growth factor 2âpositive subtypes. In multiple logistic regression, including both obesity status and diabetes as independent risk factors, Luminal A breast cancer was also associated with overweight status. Diabetes was associated with increased risk for Luminal A and Triple-Negative Breast Cancer in subgroup analyses, including women aged ≥50 years, Black women, and White women. CONCLUSIONS: Although research has identified obesity and diabetes as risk factors for breast cancer, these results underscore that comorbid risk is complex and may differ by molecular subtype. There was a significant association between diabetes and the incidence of Luminal A, Triple-Negative Breast Cancer, and human epidermal growth factor 2âpositive breast cancer in Louisiana.