Citations 2
Abstract PD8-01: Weight Trajectories in the Breast Cancer Weight Loss (BWEL) Trial (Alliance)
Cao, C., Ballman, K. V., McCall, L. M., Alfano, C., Bernstein, V., Crane, Tracy E. , Delahanty, L., Frank, L., Hahn, O., Hershman, D. L., Hopkins, J. O., Irwin, M., Mayer, E. L., Minasian, L., Nebeling, Linda , Neuhouser, M., Paskett, E. D., Spears, P. A., Stearns, V., Thomson, C. A., Wadden, Thomas A., Weiss, A. C., White, J., Hudis, C., Winer, E. P., Partridge, A. H., Carey, L. A., Ligibel, J. A., Alfano, Catherine M. , Bernstein, V., Delahanty, L.M., Goodwin, Pamela J. , Hahn, O. M., Hershman, Dawn L. , Paskett, Electra D. , Stearns, Vered , Hudis, Clifford A. , Partridge, Ann H. , Carey, L.
Clinical Cancer Research | February 17, 2026 | Volume: 32 | Issue: 4_Supplement | Pages: PD8-01-PD8-01
10.1158/1557-3265.sabcs25-pd8-01
Abstract Background: Obesity is a poor prognostic factor in early breast cancer (BC). The BWEL trial (Alliance A011401; NCT02750826) is a phase 3 randomized trial testing the impact of a weight loss intervention (WLI) on invasive disease-free survival in women with stage II-III BC and a body mass index (BMI) ≥27 kg/m2. Here we report trajectories of weight change in BWEL WLI participants (pts). Methods: Eligible pts were within 16 months of diagnosis of stage II-III HER2-negative BC, had completed chemotherapy (chemo) and radiation (if given), and were randomized 1:1 to a telephone-based WLI, focused on caloric restriction and exercise, plus health education (HE) or to an HE-alone control group. WLI pts were assigned a trained coach at the BWEL call center and received 42 phone calls over the 2-year (yr) WLI period. Weight and height at baseline, 6 and 24 months were collected by study staff. All WLI pts were provided with a Fitbit wireless scale. Fitbit weight records (FWRs) were automatically imported to the BWEL portal for pts with wireless access and self-reported in the portal for pts without wireless access. FWRs were averaged (avg) by week (wk) from the WLI start date up to 104 wks. Baseline pt factors were self-reported; treatment history was abstracted from the medical record. Linear mixed-effect models were used to evaluate trajectories of weight change over the 104-wk WLI. Principal component analysis and multinomial models were used to examine distinct clusters of weight trajectories. Results: 3180 pts were enrolled from 637 sites between 8/2016 and 2/2021. FWRs were available from 1508 of 1591 WLI pts, with a total of 366,294 FWRs collected during the 2-yr WLI period. In pts with FWRs, mean baseline BMI was 34.4 ± 5.6 kg/m2, mean age was 53.2 ± 10.3 yrs, 10.8% self-identified as Non-Hispanic (NH) Black and 6.1% as Hispanic, 81.1% received chemo and 56.9% were postmenopausal. No statistically significant differences in baseline factors were observed between pts with and without FWRs. Intraclass correlation coefficient of baseline weights collected by study staff and by Fitbit scales was 0.99. In the WLI cohort, avg weekly weight (kg) decreased from 91.4 (95% CI: 90.6-92.3) at baseline to 85.6 (95% CI: 84.8-86.5) by wk 40, corresponding to a peak loss of 6.1% (95% CI: 5.7-6.4) of baseline weight. Weight remained stable until wk 52 and then gradually increased to 87.0 kg (95% CI: 86.2-87.9) at wk 104, corresponding to a 4.4% (95% CI: 4.0-4.8) loss at wk 104 vs. baseline. Principal component analysis identified 3 distinct weight trajectories: 67.6% of pts experienced peak weight loss of 6.6% (95% CI: 6.3-6.9) of baseline weight, 10.0% experienced peak loss of 17.5% (95% CI: 16.8-18.2) of baseline weight, and 22.4% did not achieve weight loss, gaining on avg 2.2% (95% CI: 1.7-2.6) of baseline weight. Pts with college (relative risk ratio [RRR]=1.41, 95% CI: 1.03-1.92) and post-graduate education (RRR= 1.58, 95% CI: 1.13-2.20) and those who were premenopausal (RRR=1.70, 95% CI: 1.28-2.26) were more likely to be in the cluster that did not lose weight. Pts who were NH White (RRR=3.60, 95% CI: 1.95-6.68), postmenopausal (RRR=1.94, 95% CI: 1.28-2.95), had no alcohol use (RRR=1.49, 95% CI: 1.03-2.16), had not received chemo (RRR=1.76, 95% CI: 1.15-2.72), and had <3 chronic conditions (RRR: 2.12, 95% CI: 1.23-3.66) were more likely to be in the cluster with the highest weight loss. Conclusion: Longitudinal weight data from BWEL demonstrate peak weight loss of 6.1% in the WLI cohort at 40 wks, with distinct trajectories indicating differential responses to the WLI. This work demonstrates the feasibility of using digital health tools to track outcomes in the setting of a large-scale weight loss intervention study and informs future precision behavioral interventions in oncology. Support: U10CA180821, U10CA180882, UG1CA189823; U10CA180863. https://acknowledgments.alliancefound.org. Citation Format: C. Cao, K. Ballman, L. McCall, C. Alfano, V. Bernstein, T. Crane, L. Delahanty, L. Frank, P. Goodwin, O. Hahn, D. Hershman, J. Hopkins, M. Irwin, E. Mayer, L. Minasian, L. Nebeling, M. Neuhouser, E. Paskett, P. Spears, V. Stearns, C. Thomson, T. Wadden, A. Weiss, J. White, C. Hudis, E. Winer, A. Partridge, L. Carey, J. Ligibel. Weight Trajectories in the Breast Cancer Weight Loss (BWEL) Trial (Alliance) [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PD8-01.
Impact of Excessive Weight Gain on Cardiovascular Outcomes in Type 1 Diabetes: Results From the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study
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M., Jacobson, A., Rand, L., Rosenzwieg, J., Nathan, D.M., Larkin, M.E., Christofi, M., Folino, K., Godine, J., Lou, P., Stevens, C., Anderson, E., Bode, H., Brink, S., Cornish, C., Cros, D., Delahanty, L., deManbey, A., Haggan, C., Lynch, J., McKitrick, C., Norman, D., Moore, D., Ong, M., Taylor, C., Zimbler, D., Crowell, S., Fritz, S., Hansen, K., Gauthier‐Kelly, C., Service, F. J., Ziegler, G., Barkmeier, A., Schmidt, L., French, B., Woodwick, R., Rizza, R., Schwenk, W. F., Haymond, M., Pach, J., Mortenson, J., Zimmerman, B., Lucas, A., Colligan, R., Luttrell, L., Lopes-Virella, M., Caulder, S., Pittman, C., Patel, N., Lee, K., Nutaitis, M., Fernandes, J., Hermayer, K., Kwon, S., Blevins, A., Parker, J., Colwell, J., Lee, D., Soule, J., Lindsey, P., Bracey, M., Farr, A., Elsing, S., Thompson, T., Selby, J., Lyons, T., Yacoub-Wasef, S., Szpiech, M., Wood, D., Mayfield, R., Molitch, M., Adelman, D., Colson, S., Jampol, L., Lyon, A., Gill, M., Strugula, Z., Kaminski, L., MIRZA, R., Simjanoski, E., Ryan, D., Johnson, C., Wallia, A., Ajroud-Driss, S., Astelford, P., Leloudes, N., Degillio, A., Schaefer, B., Mudaliar, S., Lorenzi, G., Goldbaum, M., Jones, K., Prince, M., Swenson, M., Grant, I., Reed, R., Lyon, R., Kolterman, O., Giotta, M, Clark, T., Friedenberg, G., Sivitz, W.I., Vittetoe, B., Kramer, J., Bayless, M., Zeitler, R., Schrott, H., Olson, N., Snetselaar, L., Hoffman, R., MacIndoe, J., Weingeist, T., Fountain, C., Miller, R., Johnsonbaugh, S., Patronas, M., Carney, M., Mendley, S., Salemi, P., Liss, R., Hebdon, M., Counts, D., Donner, T., Gordon, J., Hemady, R., Kowarski, A., Ostrowski, D., Steidl, S., Jones, B., Herman, W.H., Martin, C.L., Pop-Busui, R., Greene, D. 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Diabetes Care | November 15, 2017 | Volume: 40 | Issue: 12 | Pages: 1756-1762
OBJECTIVE Intensive treatment (INT) of type 1 diabetes reduces the incidence of cardiovascular disease (CVD) events compared with conventional treatment (CONV), but it also results in more weight gain. Our objective was to examine whether excessive weight gain from INT of type 1 diabetes is independently associated with subsequent CVD events. RESEARCH DESIGN AND METHODS Quartiles (Q) of weight gain in 1,213 participants aged 18 years and older at enrollment in the Diabetes Control and Complications Trial (DCCT) were determined within randomized treatment groups (INT vs. CONV) using change in BMI from baseline to the closeout DCCT visits. Effects of this weight gain on CVD risk factors and outcomes during an additional 20 years of observational follow-up were then determined. RESULTS The Q4 INT group experienced greater proportional weight gain (median change in BMI, 6.08 kg/m2), increases in CVD risk factors, and need for medications for hypertension and lipids compared with the Q1–3 INT and comparable CONV groups. Over a mean of 26 years of follow-up, the numbers of major and total CVD events were not statistically different in Q4 compared with Q1–3 of either the INT or CONV group. By year 14, however, the incident CVD event curve became significantly higher in the Q4 INT group than in the Q1–3 INT groups (P = 0.024) and was similar to that for the CONV group. CONCLUSIONS For the first 13 years after DCCT, INT for type 1 diabetes reduced macrovascular events compared with CONV, even when excessive weight gain occurred. After this, total CVD events significantly increased in the Q4 INT group, becoming equivalent to those in the CONV group. Longer follow-up is needed to determine whether this trend continues and results in more major CVD events.