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THE EFFICACY GAP BETWEEN CLINICAL TRIAL AND
REAL-WORLD RESULTS FOR GLP-1 RAs AND DPP-4is GLP-1 RA DPP-4i N=2600 N=221 N=1889 N=652 Baseline HbA1c 8.4% 8.3% 7.8% 8.2% –1.2 –0.4 –0.8 –0.2 Change in HbA1c (%) –1.0 –0.6 –1.4 –1.6 –1.2 –0.4 –0.8 –0.2 Change in HbA1c (%) –1.0 –0.6 –1.4 –1.6 –1.25% –0.52% –0.68% –0.51% GAP GAP A recent study validated the concept of unrealized efficacy. The study objectives were to 1) compare the HbA1c drop seen in clinical trials for the GLP-1 RAs and DDP-4i classes with that observed in the real world, and 2) quantify the contribution of various factors to that gap. This study found pronounced gaps between clinical trials and real-world results for both drug classes. In clinical trials, patients receiving GLP-1 RAs demonstrated a 1.25% reduction in. In the real world, the HbA1c reduction was only 0.52%. Thus, the gap between the clinical trial and the real world was 0.73% In clinical trials, patients receiving DPP-4is demonstrated a 0.68% reduction in HbA1c; in contrast, a 0.51% reduction was observed in the real world. Here, we see a 0.17% gap between the clinical trial data and the real-world results Of note, both drug classes demonstrated similar reductions in HbA1c (approximately 0.5%) in the real world. The more profound drop observed in the clinical trial setting for the GLP-1 RA class was lost in the real-world setting. Background This retrospective study identified 11 pivotal randomized control trials with patients who initiated a GLP-1 RA or DPP-4i and included measurements of HbA1c. There were 7 GLP-1 RA studies (n=2600) and 4 DDP-4i studies (n=1889). A linear regression model estimated the change in HbA1c at 1 year after drug class initiation to determine real-world results and contributing factors to the efficacy gap between clinical trials and the real world Data from the 2007 to 2014 Optum Humedica database served as a resource for the real-world data and identified a cohort of patients with characteristics similar to the pivotal clinical trials An important distinction between GLP-1 RA and DPP-4i was that baseline HbA1c was similar in the real-world and clinical trial groups for GLP-1 RAs, but most of the DPP-4i trials were conducted in populations with lower baseline HbA1c levels than those found in the real world Reference Carls GS, Tuttle E, Tan RD, et al. Differences in T2DM therapy outcomes in trials vs. the real-world (RW): identifying the impact of poor adherence. Poster presented at: American Diabetes Association 76th Scientific Sessions; June 10-14, 2016; New Orleans, LA. Poster 117-LB. 11 CLINICAL TRIALSa (6-12 months) REAL WORLDb (12 months) Carls GS et al. 76th ADA Scientific Sessions. June 10–14, Poster 117-LB. aIdentified 11 pivotal randomized controlled trials with published change in HbA1c (7 GLP-1 RA [2600 patients] and 4 DPP-4i [1889 patients]). bOptum/Humedica SmartFile database ( ) was used (GLP-1 RA 221 patients; DPP-4i 652 patients). Change in HbA1c measured from drug initiation to 365±90 days later.
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REAL-WORLD TRIAL DESIGN: INVESTIGATING THE EFFICACY GAP BETWEEN CLINICAL TRIAL AND
REAL-WORLD RESULTS REAL-WOrlD Results Predicted using typical trial conditionsa Clinical Trial Population Determine Contributors to Efficacy Gap Linear Regression Model Baselineb Additional T2D Treatmentc Adherencec Match Characteristics Real-world population To quantify the contribution of various factors to the gap between the clinical trial data and real-world results seen in slide 11, a multivariate regression model generated by the clinical trial and real-world data was developed. This model controlled for various parameters, including baseline characteristics (such as age, diabetes complications, and prior drug therapy), addition of diabetes medications, and differences in adherence. The model allowed for the ability to predict a decrease in HbA1c in real-world patients if these parameters were exactly matched to those in the randomized clinical trials. By looking at each of these factors (that is, baseline characteristics, drug therapy, and adherence) individually, how much any one factor contributed to the gap between clinical trial and real-world data could be measured. Reference Carls GS, Tuttle E, Tan RD, et al. Differences in T2DM therapy outcomes in trials vs. the real-world (RW): identifying the impact of poor adherence. Poster presented at: American Diabetes Association 76th Scientific Sessions; June 10-14, 2016; New Orleans, LA. Poster 117-LB. aLinear regression model fitted to estimate the change in HbA1c 1 year after initiating GLP-1 RA or DPP-4i based on baseline and treatment characteristics.bBaseline characteristics included age, baseline HbA1c, any diabetes complications, and baseline drug therapy. cTreatment characteristics included medication adherence (classified as poorly adherent if percentage of days covered [PDC] <80%) and addition of other diabetes drugs post index date. Carls GS et al. 76th ADA Scientific Sessions. June 10–14, 2016; Poster 117-LB.
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{ POOR ADHERENCE IS THE KEY CONTRIBUTOR TO THE EFFICACY GAP: GLP-1 RAs
REAL-WORLD RESULTS PREDICTED UNDER TYPICAL TRIAL CONDITIONSa REAL WORLDb EXPLAINING THE GAP –1.2 –0.4 –0.8 –0.2 Change in HbA1c (%) –1.0 –0.6 –1.4 –1.6 -0.52% { 75% ADHERENCEc GAP -1.04% 25% BASELINE CHARACTERISTICS, ADDITIONAL DRUG THERAPY For the GLP-1 RA class, the model predicted that if parameters exactly matched what was observed in the clinical trial, there would have been a 1.04% drop in HbA1c level, which is squarely within the range found in the randomized clinical trials. The drop in the real-world HbA1c level was half that at 0.52%, leaving a 0.52% gap. The contribution of factors to the gap was then calculated. Only 25% of the gap was due to differences in baseline characteristics and additional drug therapy, while 75% of the gap was due to poor adherence. Of note, in this real-world population, adherence (that is, the proportion of days covered [PDC] by drug was ≥ 80%) for GLP-1 RA was just 29%. Background Modeling predicted that adherence accounts for −0.39% of the HbA1c gap between real-world (−0.52%) and modeled (−1.04%) clinical trials; thus, adherence accounts for 75% (−0.39%/−0.52%) of the efficacy gap The balance of the gap, 25%, was accounted for by baseline characteristics and additional drug therapy Reference Carls GS, Tuttle E, Tan RD, et al. Differences in T2DM therapy outcomes in trials vs. the real-world (RW): identifying the impact of poor adherence. Poster presented at: American Diabetes Association 76th Scientific Sessions; June 10-14, 2016; New Orleans, LA. Poster 117-LB. GLP-1 RA Adherence Rate in Real World = 29% RCT, randomized clinical trial. aLinear regression model fitted to estimate the change in HbA1c 1 year after initiating GLP-1 RA or DPP-4i based on baseline and treatment characteristics. bOptum/Humedica SmartFile database ( ) was used (GLP-1 RA 221 patients; DPP-4i 652 patients). Change in HbA1c measured from drug initiation to 365±90 days later. cMedical adherence classified as poorly adherent if percentage of days covered (PDC) <80%. Carls GS et al. 76th ADA Scientific Sessions. June 10–14, New Orleans, LA. Poster 117-LB.
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POOR ADHERENCE: KEY CONTRIBUTOR TO EFFICACY GAP IS CONSISTENT FOR BOTH GLP-1 RAs AND DPP-4is
75% OF THE GAP DUE TO POOR ADHERENCEa A similar analysis of the DPP-4i class also showed that poor adherence was responsible for 75% of the disconnect. Thus, regardless of class of diabetes medication, adherence accounted for 75% of the efficacy gap at 1 year. Background Modeling predicted that adherence accounts for −0.13% of the HbA1c gap between real-world (−0.51%) and modeled (−0.68%) clinical trials; thus, adherence accounts for 75% (−0.13%/−0.18%) of the efficacy gap The balance of the gap, 25%, was accounted for by baseline characteristics and additional drug therapy Reference Carls GS, Tuttle E, Tan RD, et al. Differences in T2DM therapy outcomes in trials vs. the real-world (RW): identifying the impact of poor adherence. Poster presented at: American Diabetes Association 76th Scientific Sessions; June 10-14, 2016; New Orleans, LA. Poster 117-LB. 25% OF THE GAP DUE TO DIFFERENCES IN BASELINE AND TREATMENT CHARACTERISTICSb aLinear regression model fitted to estimate the change in HbA1c 1 year after initiating GLP-1 RA based on baseline and treatment characteristics. bBaseline characteristics measured at time of drug initiation, and treatment characteristics included treatment with other T2D drugs. Carls GS et al. 76th ADA Scientific Sessions. June 10–14, Poster 117-LB.
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