889 research outputs found
C. C. Mehta
No full textOn the life and works of Chandravadan Chimanlal Mehta, b. 1901, Gujarati author
Comparative Effectiveness of Angiotensin Converting Enzyme Inhibitors and Angiotensin Receptor Blockers on the Risk of Dementia in Patients with Type 2 Diabetes and Hypertension
No full textObjectives: Specific aims of the study were: (1) To develop RxDx risk index to predict dementia in patients with type 2 diabetes mellitus and hypertension (2) To compare RxDx risk index with different versions of Charlson comorbidity score (CCS) and chronic disease score (CDS) to predict dementia and (3) To compare Angiotensin Converting Enzyme (ACE) inhibitors versus Angiotensin Receptor Blockers (ARB) for the risk of dementia in patients with type 2 diabetes mellitus and hypertension.
Methods: The Clinical Practice Research database was used for this retrospective longitudinal cohort study. Elderly patients (age>=65 years) diagnosed with type 2 diabetes and hypertension without prior diagnosis for dementia were included in the cohort. The Cox proportional hazard model was constructed to model time to dementia by incorporating age, gender and 31 RxDx disease conditions. Points were assigned to risk factors based on beta coefficients to obtain summary risk score. Different rick indices were compared against RxDx-Dementia risk index using c statistics, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). A marginal structural model was constructed while controlling for demographic and clinical baseline variables and time-varying blood pressure variable to estimate causal effect of ACE inhibitors compared to ARB on the risk of dementia.
Results: The incidence of dementia was 3.42% in patients with type 2 diabetes mellitus and hypertension. The c-statistics value for RxDx-Dementia risk index was 0.795 (95% confidence interval [CI], 0.789-0.801) and 0.806 (95% CI, 0.798-0.814). Based on the c-statisctics, NRI and IDI values the RxDx-Dementia risk index performed better compared to summary CCS, CDS scores and its combinations. The marginal structural model estimated statistically significant 39% (OR, 0.61; 95%CI, 0.50-0.77) reduction in the risk of developing dementia compared to ACE inhibitors.
Conclusions: RxDx-Dementia risk index can be a useful tool to identify hypertensive diabetic patients who are at high risk of developing dementia as well as to control confounding in observational studies. ARB may offer protective effect on the risk of dementia compared to ACE inhibitors in patients with type 2 diabetes and hypertension. When there is no treatment available for dementia, prevention or delaying onset of dementia may help reduce the overall disease burden.Pharmacy, College o
TREATMENT OF TYPE 2 DIABETES AMONG MEDICARE BENEFICIARIES WITH AND WITHOUT ALZHEIMER’S DISEASE: A RETROSPECTIVE COHORT STUDY
No full textBackground: While many individuals with Alzheimer’s disease (AD) have type 2 diabetes (T2DM), little is known regarding whether and how the treatment of T2DM varies by AD status.
Objective: To compare T2DM treatment among individuals with and without AD.
Methods: We conducted a retrospective cohort study using 20% Medicare Fee-for-Service (FFS) claims data from January 2017 through January 2019. We included individuals aged ≥66 years who were newly diagnosed with T2DM with continuous enrollment for at least one year prior to their T2DM diagnosis. Individuals with prior diagnoses of type 1 diabetes or T2DM were excluded. AD was identified using the 12 months preceding T2DM diagnosis. We assessed the initiation of antidiabetic therapy within one year of incident T2DM diagnosis and described utilization patterns by drug class. Multivariable logistic regression models were used to estimate adjusted odds ratios for the association between AD status and overall antidiabetic drug initiation, as well as initiation of specific drug classes, controlling for demographic and clinical covariates.
Results: Among 388,359 Medicare beneficiaries newly diagnosed with T2DM, 9,584 had a diagnosis of AD. Patients with AD were older (mean age 83.2 vs. 75.8) and more often female (64.4% vs. 53.4%) compared to those without AD. Antidiabetic treatment initiation within one year was lower in individuals with AD compared to those without AD (41.7% vs. 64.4%). At first treatment initiation, patients with AD were more likely to receive insulin (32.3% vs. 18.6%) but were less likely to initiate metformin (41.9% vs. 53.4%), SGLT2 inhibitors (0.6% vs. 2.1%), and GLP-1 receptor agonists (0.8% vs. 2.4%). In adjusted models, AD was associated with significantly lower odds of antidiabetic treatment initiation (OR 0.55, 95% CI 0.53–0.57) and lower odds of initiating newer drugs like GLP-1 receptor agonists (OR 0.50, 95% CI 0.34–0.71) and SGLT2 inhibitors (OR 0.48, 95% CI 0.31–0.69).
Conclusion: Among this large, diverse cohort of Medicare beneficiaries in the U.S., there were notable differences in diabetes treatment among older adults with and without AD. Insulin use was more common, while metformin and newer agents such as SGLT2 inhibitors and GLP-1 receptor agonists were less frequently prescribed in AD patients. Future work should explore the basis for these differences, which may reflect a combination of patient, provider and system-level factors
TREATMENT OF TYPE 2 DIABETES AMONG MEDICARE BENEFICIARIES WITH AND WITHOUT ALZHEIMER’S DISEASE: A RETROSPECTIVE COHORT STUDY
No full textBackground: While many individuals with Alzheimer’s disease (AD) have type 2 diabetes (T2DM), little is known regarding whether and how the treatment of T2DM varies by AD status.
Objective: To compare T2DM treatment among individuals with and without AD.
Methods: We conducted a retrospective cohort study using 20% Medicare Fee-for-Service (FFS) claims data from January 2017 through January 2019. We included individuals aged ≥66 years who were newly diagnosed with T2DM with continuous enrollment for at least one year prior to their T2DM diagnosis. Individuals with prior diagnoses of type 1 diabetes or T2DM were excluded. AD was identified using the 12 months preceding T2DM diagnosis. We assessed the initiation of antidiabetic therapy within one year of incident T2DM diagnosis and described utilization patterns by drug class. Multivariable logistic regression models were used to estimate adjusted odds ratios for the association between AD status and overall antidiabetic drug initiation, as well as initiation of specific drug classes, controlling for demographic and clinical covariates.
Results: Among 388,359 Medicare beneficiaries newly diagnosed with T2DM, 9,584 had a diagnosis of AD. Patients with AD were older (mean age 83.2 vs. 75.8) and more often female (64.4% vs. 53.4%) compared to those without AD. Antidiabetic treatment initiation within one year was lower in individuals with AD compared to those without AD (41.7% vs. 64.4%). At first treatment initiation, patients with AD were more likely to receive insulin (32.3% vs. 18.6%) but were less likely to initiate metformin (41.9% vs. 53.4%), SGLT2 inhibitors (0.6% vs. 2.1%), and GLP-1 receptor agonists (0.8% vs. 2.4%). In adjusted models, AD was associated with significantly lower odds of antidiabetic treatment initiation (OR 0.55, 95% CI 0.53–0.57) and lower odds of initiating newer drugs like GLP-1 receptor agonists (OR 0.50, 95% CI 0.34–0.71) and SGLT2 inhibitors (OR 0.48, 95% CI 0.31–0.69).
Conclusion: Among this large, diverse cohort of Medicare beneficiaries in the U.S., there were notable differences in diabetes treatment among older adults with and without AD. Insulin use was more common, while metformin and newer agents such as SGLT2 inhibitors and GLP-1 receptor agonists were less frequently prescribed in AD patients. Future work should explore the basis for these differences, which may reflect a combination of patient, provider and system-level factors
ASSOCIATION BETWEEN METFORMIN USE AND MORTALITY AMONG INDIVIDUALS WITH NON-SMALL CELL LUNG CANCER RECEIVING IMMUNE CHECKPOINT INHIBITORS: A RETROSPECTIVE COHORT STUDY
No full textIntroduction. Metformin has potential to synergistically enhance the effect of immune checkpoint inhibitors (ICI) in non-small cell lung cancer (NSCLC). We evaluated the association between metformin use prior to ICI initiation and cancer-specific and all-cause mortality among NSCLC patients.
Methods. We conducted a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data (2013 to 2019), including NSCLC patients with type 2 diabetes who newly initiated ICI therapy and had prior antidiabetic medication use. The exposure was metformin monotherapy versus sulfonylurea and/or dipeptidyl peptidase-4 (DPP-4) inhibitors. The primary outcome was cancer-specific mortality, and the secondary outcome was all-cause mortality. We used stabilized inverse probability of treatment weighting (sIPTW) to adjust for confounders. Fine-Gray competing risk model estimated cancer-specific mortality, while Cox proportional hazards model evaluated all-cause mortality.
Results. We included 1,123 metformin users and 362 sulfonylurea/DPP-4 users. Although baseline characteristics differed, groups were well balanced after weighting. The adjusted incidence rate (aIR) of cancer-specific mortality was 82 vs. 81 (aIR difference = 1, 95% CI: -13 – 16), and all-cause mortality was 71 vs. 67 (aIR difference = 4, 95% CI: -6 – 15) per 100 person-years for metformin and sulfonylurea/DPP-4 users, respectively. Metformin use was not significantly associated with cancer-specific mortality (adjusted hazard ratio (aHR) = 1.08, 95% CI: 0.88–1.33) and all-cause mortality (aHR = 1.07, 95% CI: 0.90–1.26).
Conclusions. In this large, diverse cohort of individuals with NSCLC using ICI, there was no statistically significant association between metformin use and cancer-specific or all-cause mortality
The Effects of Drug-Drug Interactions Between Direct-Acting Oral Anticoagulants and Antiseizure Medications: A Target Trial Emulation
No full textAll direct oral anticoagulants (DOAC) and some antiseizure medications (ASM) interact with cytochrome P450 3A4 (CYP3A4) or P-glycoprotein (P-gp). Concomitant use of these medications may cause drug-drug interactions that increase the risk for thromboembolism. Existing studies assessing this association are conflicting, limited by small sample size, or are conducted on non-US populations.
This new-user, retrospective cohort study emulates a target trial using Merative MarketScan insurance claims data from 2011 to 2019. We included US adults currently using a DOAC who initiated treatment with an ASM that interacts with CYP3A4 or P-gp or an ASM that does not interact with CYP3A4 or P-gp. We excluded persons who were not continuously insured for a year prior to the start of follow-up or who had history of concomitant DOAC and ASM use. We evaluated time-to-event for thromboembolism as well as the incidence rate in this taking interacting and non-interacting drug combinations. We calculated inverse probability of treatment weights using baseline age, sex, comorbidities, and comedications. We used these in a weighted Cox regression to compute an adjusted hazards ratio.
Among the 33,117 participants included in the study, 5,388 (16%) initiated an interacting drug combination and 27,729 (84%) initiated a non-interacting drug combination. The incidence of thromboembolism per 100 person-years was 2.01 (95% CI: 0.51, 8.01) in the interacting group and 0.88 (95% CI: 0.11, 7.11) in the non-interacting group. After weighting, we found that those taking an interacting combination had 1.46 (95% CI: 0.85, 2.51) times the hazard for a thromboembolic event compared to those taking a non-interacting combination.
Among US adults, concomitantly using a DOAC with an antiseizure medication that interacts with P-gp and CYP3A4 appeared to increase the risk for thromboembolism, but the effect did not achieve statistical significance, possibly due to the limited event count. Additional studies collecting more events are needed to confirm the results of this study
The Effects of Drug-Drug Interactions Between Direct-Acting Oral Anticoagulants and Antiseizure Medications: A Target Trial Emulation
No full textAll direct oral anticoagulants (DOAC) and some antiseizure medications (ASM) interact with cytochrome P450 3A4 (CYP3A4) or P-glycoprotein (P-gp). Concomitant use of these medications may cause drug-drug interactions that increase the risk for thromboembolism. Existing studies assessing this association are conflicting, limited by small sample size, or are conducted on non-US populations.
This new-user, retrospective cohort study emulates a target trial using Merative MarketScan insurance claims data from 2011 to 2019. We included US adults currently using a DOAC who initiated treatment with an ASM that interacts with CYP3A4 or P-gp or an ASM that does not interact with CYP3A4 or P-gp. We excluded persons who were not continuously insured for a year prior to the start of follow-up or who had history of concomitant DOAC and ASM use. We evaluated time-to-event for thromboembolism as well as the incidence rate in this taking interacting and non-interacting drug combinations. We calculated inverse probability of treatment weights using baseline age, sex, comorbidities, and comedications. We used these in a weighted Cox regression to compute an adjusted hazards ratio.
Among the 33,117 participants included in the study, 5,388 (16%) initiated an interacting drug combination and 27,729 (84%) initiated a non-interacting drug combination. The incidence of thromboembolism per 100 person-years was 2.01 (95% CI: 0.51, 8.01) in the interacting group and 0.88 (95% CI: 0.11, 7.11) in the non-interacting group. After weighting, we found that those taking an interacting combination had 1.46 (95% CI: 0.85, 2.51) times the hazard for a thromboembolic event compared to those taking a non-interacting combination.
Among US adults, concomitantly using a DOAC with an antiseizure medication that interacts with P-gp and CYP3A4 appeared to increase the risk for thromboembolism, but the effect did not achieve statistical significance, possibly due to the limited event count. Additional studies collecting more events are needed to confirm the results of this study
ASSOCIATION BETWEEN METFORMIN USE AND MORTALITY AMONG INDIVIDUALS WITH NON-SMALL CELL LUNG CANCER RECEIVING IMMUNE CHECKPOINT INHIBITORS: A RETROSPECTIVE COHORT STUDY
No full textIntroduction. Metformin has potential to synergistically enhance the effect of immune checkpoint inhibitors (ICI) in non-small cell lung cancer (NSCLC). We evaluated the association between metformin use prior to ICI initiation and cancer-specific and all-cause mortality among NSCLC patients.
Methods. We conducted a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER)-Medicare data (2013 to 2019), including NSCLC patients with type 2 diabetes who newly initiated ICI therapy and had prior antidiabetic medication use. The exposure was metformin monotherapy versus sulfonylurea and/or dipeptidyl peptidase-4 (DPP-4) inhibitors. The primary outcome was cancer-specific mortality, and the secondary outcome was all-cause mortality. We used stabilized inverse probability of treatment weighting (sIPTW) to adjust for confounders. Fine-Gray competing risk model estimated cancer-specific mortality, while Cox proportional hazards model evaluated all-cause mortality.
Results. We included 1,123 metformin users and 362 sulfonylurea/DPP-4 users. Although baseline characteristics differed, groups were well balanced after weighting. The adjusted incidence rate (aIR) of cancer-specific mortality was 82 vs. 81 (aIR difference = 1, 95% CI: -13 – 16), and all-cause mortality was 71 vs. 67 (aIR difference = 4, 95% CI: -6 – 15) per 100 person-years for metformin and sulfonylurea/DPP-4 users, respectively. Metformin use was not significantly associated with cancer-specific mortality (adjusted hazard ratio (aHR) = 1.08, 95% CI: 0.88–1.33) and all-cause mortality (aHR = 1.07, 95% CI: 0.90–1.26).
Conclusions. In this large, diverse cohort of individuals with NSCLC using ICI, there was no statistically significant association between metformin use and cancer-specific or all-cause mortality
DEVELOPMENT AND VALIDATION OF A MODERN PRESCRIPTION-BASED RISK SCORE TO PREDICT HEALTHCARE SPENDING
No full textPrescription-drug based risk scores offer an important alternative to diagnosis-based risk scoring systems when diagnostic information is unavailable; however, their value depends upon a given score’s ability to capture the current therapeutic landscape. We performed a retrospective cohort study using Merative MarketScan administrative claims data from continuously enrolled, commercially insured adults between January 2021 and December 2022 to develop and validate a modern, prescription-based risk score for predicting healthcare expenditures. Prescription use was described using over 300 binary drug categories, and total healthcare spending was the primary outcome. We characterized the cohort with descriptive statistics and fit several machine learning models that vary in their approaches to regularization and decision-making, including elastic net regression, random forest, and extreme gradient boosting, using 60% of the sample for model development and 40% for validation. Predictor weights were assigned based on beta coefficients from the elastic net regression model, with expenditures modeled on a logarithmic scale. The drug-only risk score achieved an R2 of 0.135 in the validation dataset, improving to 0.173 with the addition of age and sex. These results are comparable to many existing prescription-based risk scores predicting future total healthcare expenditures. Our findings underscore the potential of updated prescription-based risk scores for expenditure prediction and support further research to optimize model performance
HETEROGENEITY OF TREATMENT EFFECTS OF GLUCAGON-LIKE PEPTIDE-1 (GLP-1) RECEPTOR AGONISTS ON WEIGHT LOSS: A RETROSPECTIVE COHORT STUDY
No full textBackground: While there is high quality evidence supporting the effectiveness of glucagon-like peptide-1 receptor agonists (GLP-1) for the treatment of obesity, less is known regarding how such effectiveness may vary across different patient subpopulations.
Objectives: To quantify heterogeneity in weight loss response among GLP-1 users, stratified by patient age, sex, race/ethnicity, diabetes, and baseline body mass index (BMI).
Methods: We used TriNetX, a database containing electronic health records from 81 academic medical centers in the United States, to identify adults with at least 6-month continuous GLP-1 use between September 2014 and November 2023. Our primary outcome was percentage change in BMI from baseline, defined as the most recent BMI measurement within 6 months prior to GLP-1 initiation, overall and across different subpopulations of interest. We used linear mixed-effects models with natural splines to examine BMI changes over time, adjusting for individuals’ demographics and clinical characteristics.
Results: Among 23,291 GLP-1 users, the mean baseline BMI was 37.3 ± 7.7 kg/m² and 65.2% were female. During the 6-month follow-up period, 42% achieved ≥5% BMI reduction. There was no statistically significant reduction in BMI between older (≥65 years) and younger adults (-4.1% vs. -4.7%, p=0.132). There were modest, though statistically significant, differences in BMI reduction by sex (females: -5.1% vs males: -3.5%, p<0.001) and race (Black: -4.1% vs White: -4.8%, p<0.001). Individuals with no diabetes experienced substantially greater weight loss than patients with diabetes (-6.7% vs -3.5%, p<0.001). Compared to patients with baseline BMI<30 (-2.0%), patients with BMI 30-35 showed greater reduction (-4.5%, p<0.001), and those with BMI≥35 showed the largest reduction (-5.2%, p<0.001).
Conclusions: Among this large, diverse cohort of adults in the United States, real-world effectiveness of GLP-1 was greater among women, Whites, individuals without diabetes, and those with higher baseline BMI. These findings can be used to inform further research as well as treatment selection among those who may be eligible for pharmacologic treatment of obesity
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