Miller, Robert S.

349527 Background: Symptoms are common during cancer care but often go undetected. Digital systems that elicit patient-reported outcomes (PRO) surveys may detect symptoms early and prompt clinicians to intervene, thereby alleviating suffering and averting complications. Methods: In a cluster-randomized trial, U.S.-based community oncology practices were randomized 1:1 to digital symptom monitoring with PRO surveys, or to usual care control. Patients receiving systemic treatment for metastatic cancer were eligible. At PRO practices, participants were invited to complete a weekly survey via web or automated telephone system for up to one year, including questions about nine common symptoms, performance status, and falls. Severe or worsening symptoms triggered electronic alerts to care team nurses, and reports showing longitudinal symptom data were available to oncologists at visits. Pre-specified secondary outcomes included impact on physical function, symptom control, and health-related quality of life (HRQL). The primary outcome of survival is not yet mature. Results: At 52 practices, 1,191 patients were eligible and enrolled (593 PRO; 598 control). Clinically meaningful benefits were experienced in physical function by 13.8% more patients with PRO versus control (P=0.009); symptom control by 16.1% (P=0.003); and HRQL by 13.4% (P=0.006). Mean changes from baseline were superior with PRO versus control for physical function (mean difference 2.47, 95% CI 0.41-4.53; P=0.02), symptom control (2.56, 0.95-4.17; P=0.002), and HRQL (2.43, 0.90-3.96; P=0.002). Patients completed 20,565/22,486 (91.5%) of expected weekly PRO surveys. Conclusions: Digital symptom monitoring during cancer treatment confers clinical benefits. Clinical trial information: NCT03249090.

PURPOSE Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)–positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake value corrected for lean body mass (SULmax) on 18 F-labeled fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) would predict pathologic complete response (pCR) to pertuzumab and trastuzumab (PT). PATIENTS AND METHODS Patients with stage II or III, estrogen receptor–negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. 18 F-labeled fluorodeoxyglucose positron emission tomography-computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percent change in SULmax by C1D15 predicting pCR is ≤ 0.65, with a one-sided type I error rate of 10%. RESULTS Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 22%. Receiver operator characteristic analysis of percent change in SULmax by C1D15 yielded an area under the curve of 0.72 (80% CI, 0.64 to 0.80; one-sided P = .12), which did not reject the null hypothesis. However, between patients who obtained pCR and who did not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 41.8%; P = .004) and SULmax reduction ≥ 40% was more prevalent (83% v 52%; P = .03; positive predictive value, 31%). Participants not obtaining a 40% reduction in SULmax by C1D15 were unlikely to obtain pCR (negative predictive value, 91%). CONCLUSION Although the primary objective was not met, early changes in SULmax predict response to PT in estrogen receptor–negative and HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate tailoring of therapy in this setting.

Abstract Defining patient-to-patient similarity is essential for the development of precision medicine in clinical care and research. Conceptually, the identification of similar patient cohorts appears straightforward; however, universally accepted definitions remain elusive. Simultaneously, an explosion of vendors and published algorithms have emerged and all provide varied levels of functionality in identifying patient similarity categories. To provide clarity and a common framework for patient similarity, a workshop at the American Medical Informatics Association 2019 Annual Meeting was convened. This workshop included invited discussants from academics, the biotechnology industry, the FDA, and private practice oncology groups. Drawing from a broad range of backgrounds, workshop participants were able to coalesce around 4 major patient similarity classes: (1) feature, (2) outcome, (3) exposure, and (4) mixed-class. This perspective expands into these 4 subtypes more critically and offers the medical informatics community a means of communicating their work on this important topic.

10509 Background: PST allows for improved surgical outcomes and response assessment without compromising long term outcomes. PST is an attractive model for assessing surrogate markers of response to therapy. We hypothesized that changes in tumor standardized uptake values corrected for lean body mass (SUL) max on FDG- PET by cycle 1 day 15 (C1D15) of therapy would predict pathological complete response (pCR) to PST in women with stage 2-3, grade 2-3, HER2-negative breast cancer. Methods: TBCRC008 is a multicenter placebo-controlled trial that investigates pCR following 12 weeks of preoperative carboplatin and albumin-bound paclitaxel with or without vorinostat. FDG-PET followed by tumor biopsies were performed at baseline and C1D15. We correlated % reduction in SULmax on FDG-PET (PERCIST 1.0; Wahl RL, J Nuc Med 2009) with pCR (no invasive cancer in breast/axilla). We compared % reduction in SULmax between responders (pCR) and non responders (no pCR) using nonparametric Wilcoxon rank sum test. We explored association of % reduction in SULmax at pre-specified cutoff with response using Fisher’s exact test and logistic regression. We correlated baseline, C1D15, and % change in Ki67 at C1D15 with pCR. Results: Accrual is complete. Of 62 women enrolled (10/2009-11/2011), 40 have completed study PST and surgery (median age 47.5 [range 30-68], ER-positive 67%). Overall pCR was 26%. In an intent to treat analysis (n=39), we observed a significant difference in median % reduction in SULmax between responders vs not (66.6% vs 32.4%, p <0.001). We observed a higher proportion of reduction in SULmax ≥ 60% in responders vs not (80% vs 3.5%, p <0.001). The differences in baseline, C1D15 and % change in Ki67 were not significant between responders and non-responders. Conclusions: Change in SULmax on FDG-PET 15 days after initiating PST was significantly greater in patients with pCR versus no pCR. Future studies will determine whether altering therapy based on early changes in SULmax will improve pCR. Unblinded data from all participants will be presented at the meeting.

PURPOSE Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)–positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake values corrected for lean body mass (SULmax) on [ 18 F]fluorodeoxyglucose positron emission tomography/computed tomography would predict pathologic complete response (pCR) to neoadjuvant pertuzumab and trastuzumab (PT). PATIENTS AND METHODS Patients with stage II/III, estrogen receptor–negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. [ 18 F]Fluorodeoxyglucose positron emission tomography/computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percentage of change in SULmax by C1D15 predicting pCR is less than or equal to 0.65, with a one-sided type I error rate of 10%. RESULTS Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 34%. Receiver operating characteristic analysis yielded an area under the curve of 0.76 (90% CI, 0.67 to 0.85), which rejected the null hypothesis. Between patients who obtained pCR versus not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 33.5%; P < .001), an SULmax reduction greater than or equal to 40% was more prevalent (86% v 46%; P < .001; negative predictive value, 88%; positive predictive value, 49%), and a significant difference in median C1D15 SULmax (1.6 v 3.9; P < .001) and higher proportion of C1D15 SULmax less than or equal to 3 (93% v 38%; P < .001; negative predictive value, 94%; positive predictive value, 55%) were observed. CONCLUSION Early changes in SULmax predict response to four cycles of PT in estrogen receptor–negative, HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate a more tailored approach to therapy in this setting.