Sit, Laura

Abstract Background. Patient-reported outcomes (PROs) are increasingly recognized as a valuable component to understand treatment tolerability and toxicity among patients on clinical trials. We have implemented a system for monitoring patient reported outcomes (PROs), symptoms, and quality of life (QOL) using electronic PRO (ePRO) instruments for patients enrolled in the I-SPY2 trial. I-SPY2 is a phase II multi-site clinical trial evaluating the effect of novel neoadjuvant therapies for locally advanced breast cancer. We correlated patient demographic factors with symptoms, investigated the trajectory of symptoms throughout treatment, and sought to characterize symptoms associated with decline in physical function (PF). Methods. Our study population included 259 I-SPY2 patients that completed surveys on one of 9 study arms (including novel oral taxane/immunotherapy combinations, IV paclitaxel, checkpoint inhibitor+/- LAG3 inhibitor, and control IV paclitaxel +/- trastuzumab/pertuzumab). After the 12 week period of investigational agents, most patients received standard adriamycin and cyclophosphamide (AC). Symptom severity, frequency, and interference was assessed weekly using 33 items from the PRO-CTCAE item bank. PF was assessed using the NIH PROMIS instrument and was evaluated at baseline, inter-regimen (after 12 weeks of treatment), pre-surgery, and 1 and 6 months at follow-up. An odds ratio was used to assess univariate associations between age and race, and symptoms. Regularized multi-variate regression was used to evaluate early symptoms (prior to week 6) predictive of a clinically significant (>5 point T-score) decline in PF from baseline to post-treatment follow-up among all races and age groups. Results. Of 259 patients (mean age (SD) = 46.8 (13.6)), 160 (58%) were White, 13 (5%) were Asian, 26 (10%) were African American (AA), 25 (9.3%) were Hispanic, and 35 (13.5%) self-reported “Other”. At baseline, AA patients had a higher severity of joint pain than White patients (OR = 14.9, P < 0.05). During study treatment with paclitaxel and/or novel agent within the first 12 weeks of treatment, AA patients and non-white (NW) patients were more likely to report severe vomiting than White patients (OR =13.22 and 12.72, P< 0.05 and P< 0.03 respectively). During treatment with AC, NW patients were more likely to report higher severity of neuropathy than White patients (OR = 5.43, P< 0.03). Among all patients, in analysis of early symptoms predictive of a clinically significant decline in PF between baseline and 1 month post treatment, predictors included high frequency of diarrhea, severity of itching, and severity of joint pain. Further analysis of symptom trajectories revealed that frequency of diarrhea reported rose sharply between baseline and Cycle 2 with 9 patients (7%) reporting occasional or frequent diarrhea to 39 patients (28%) reporting occasional to almost constant diarrhea and remained stable at that proportion for the remainder of treatment. Frequency of diarrhea declined slightly during AC (17%) and dropped to baseline levels by follow-up. In contrast, severity of joint pain persisted post-treatment, rising consistently from baseline through follow- up with 3 patients (2%) reporting moderate to severe joint pain at baseline to 18 patients (35%) reporting moderate to severe joint pain at follow-up. Conclusion. Among I-SPY2 participants, when higher grade of diarrhea is persistent (or uncontrolled), it impacts physical function even after end of therapy. In some cases, race was also a determinant in symptom trajectory, although a higher enrollment of AA and NW patients will enable more robust estimates to be computed. While some of these early symptom predictors are transient and resolve by the time of follow-up, others persist long-term and contribute more directly towards impaired physical function at follow-up. Citation Format: Amrita Basu, Saumya Umashankar, Kaylee Blevins, Anna Northrop, Anika Christofferson, Ebunoluwa Olunuga, Jaeyoon Cha, Ananya Mittal, Julissa Molina-Vega, Laura Sit, Thelma Brown, Bev Parker, Diane Heditsian, Susie Brain, Carol Simmons, Alessandra Taboada, Tina J. Hieken, Kathryn Ruddy, Carolina Salvador, Candace Mainor, Anosheh Afghahi, Sarah Tevis, Anne Blaes, Irene M. Kang, Jane Perlmutter, Hope Rugo, Sai Kanaparthi, Garry Peterson, Lisa T. Weiss, Adam Asare, Laura J. Esserman, Michelle Melisko, Dawn Hershman. The Association Between Symptom Severity and Physical Function among Participants in I-SPY2 [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-07-03.

Abstract Introduction: Advances in technology and internet capability have provided an opportunity for efficient collection of Patient Reported Outcomes (PRO) during medical treatment. Here we describe the development and implementation of a system for monitoring patient reported adverse events (AEs) and quality of life (QoL) using electronic PRO (ePRO) instruments for patients enrolled on the Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular analysis (I-SPY 2 TRIAL), a phase II adaptive platform clinical trial for locally advanced breast cancer. Methods: We designed an ePRO system to increase the accuracy of patient-reported QoL and AE data collection with the intent to act on symptoms in real time. Using the OpenClinica electronic data capture system, we developed rules-based logic to build automated ePRO surveys, customized to the I-SPY 2 treatment schedule. Weekly surveys contained a maximum of 126 validated, branching logic questions from the Patient Reported Outcomes Measurement Information System (PROMIS®) Health Measures and the National Cancer Institute’s Patient Reported Outcomes - Common Terminology Criteria for Adverse Events (PRO-CTCAE™) instruments. We piloted ePROs at the University of California, San Francisco (UCSF) to evaluate compatibility with a variety of I-SPY 2 patient scenarios (e.g., dose delays). We then staggered rollout of the ePRO system to 22 I-SPY 2 sites to ensure technological feasibility. In order to improve accuracy of data collection, we utilized real-time tracking and developed a Clinical Research Coordinator (CRC) training manual, which integrated workflow diagrams with technical solutions. CRCs were trained using remote video sessions. Results: The UCSF ePRO pilot began in September of 2020. Over 9-months, we accrued 43 I-SPY 2 patients (average age of 43.8 years), whose interactions with the ePRO system informed design improvements. Of the patients who received a baseline ePRO survey, the completion rate was 75.9% (average age of 44.2 years). This represents an increase from the 15-20% baseline completion rate for the 360 UCSF I-SPY 2 patients who received paper-based PRO surveys between May 2012 - January 2019. As of June 2021, the ePRO system was operational at all 22 I-SPY 2 sites. The UCSF pilot revealed that engagement with patients at critical timepoints improved survey completion. CRCs facilitated patient participation by sending instructional emails and communicating with patients weekly. We tracked data completeness using a Patient Tracking report, which displayed each patient’s survey completion history. This real-time tool enabled CRCs to identify patients who had not completed ePRO surveys prior to their visit, so they could be provided a tablet computer to complete the survey in the clinic. After introducing tablets into the workflow at UCSF, patient completion of the baseline survey increased from 75.9% to 80%. Conclusion: The transition from paper to electronic QOL and AE data collection improves the ability of patients to complete PRO surveys, but the process must also be optimized and integrated into clinical workflow and trial conduct. In the future, we will present additional results highlighting the feasibility of multilingual ePRO integration into I-SPY 2. ePRO also provides a new opportunity for data analysis, as well as the potential to reduce high grade toxicity through early intervention. It will allow us to assess QoL and AE data by drug regimen, site, provider, and study treatment. The creation of clinician-facing reports also enables access to patient responses in real-time. By implementing ePRO within I-SPY 2, we not only increase efficiency and accuracy of patient-reported data collection, but also improve quality of care and patient safety. Citation Format: Anna Northrop, Anika Christofferson, Michelle Melisko, Laura Sit, Ebunoluwa Olunuga, Ananya Mittal, Adi Goldman, Thelma Brown, Diane Heditsian, Bev Parker, Susie Brain, Carol Simmons, Alessandra Taboada, Kathryn J Ruddy, Tina Hieken, Mara Piltin, Kiri Cook, Carolina Salvador, Candace Mainor, Anosheh Afghahi, Sarah Tevis, Anne Blaes, Irene Kang, Susan Melin, Laura Esserman, Adam Asare, Dawn L Hershman, Amrita Basu. Improving patient-reported outcome data capture for clinical research: ePRO in ISPY 2, a phase 2 breast cancer study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-12-02.

Abstract Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype. Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses. Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%. Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors. Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100% Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-04.

Abstract Background: A variety of investigational HER2-inhibitor agents/combinations have been tested in I-SPY 2, including neratinib (N), TDM1 combined with pertuzumab (P) (TDM1/P), and trastuzumab (H) combined with pertuzumab (H/P; prior to this combination becoming standard of care), all with trastuzumab as control (Ctr). All three experimental arms graduated, showing improved efficacy over control in one or more receptor subsets (HR+HER2+, HR-HER2+, or/and HER2+). Here we assess 10 biomarkers in the HER2, ER/PR, and proliferation pathways on multiple levels of resolution (expression, protein, phospho-protein) as predictors of response in these four arms, hypothesizing that highly HER2-activated, proliferative tumors may be more sensitive to HER2-inhibition than those that are more luminal and quiescent. Methods: 192 HER2+ patients were considered in this analysis: (31 Ctr, 65 N, 52 TDM1/P, and 44 H/P). 10 biomarkers relating to HER2, ER, or proliferation were evaluated from pre-treatment biopsies: HER2 IHC (n=145), 3 expression signatures (n=192), BluePrint subtype (n=192), and 5 protein/phospho-protein analytes by RPPA (n=175). Each biomarker was tested for association with pCR in the whole population and within each arm using a logistic model. This analysis was adjusted for HR status and treatment arm as covariates, and performed within receptor subtypes. This analysis does not adjust for multiplicities of other biomarkers. Results: In the population as a whole, HER2 and HER2-signaling biomarkers, evaluated at multiple levels of resolution: IHC, total-/phospho-protein by RPPA, and mRNA (HER2 amplicon module) - are highly correlated (rho=0.8 [0.65-0.92]). Higher HER2 levels and activity are associated with response: HER2 IHC 3+ status (LR p=0.00032), total quantitative ERBB2 protein by RPPA (LR p=5.4E-09), ERBB2 activation levels (LR p=6.58E-06 (pERBB2 (Y1248)) and 9.95E-06 (pEGFR Y1173)), and the ERBB2 amplicon expression signature (LR p=2.38E-08). In contrast, higher average ER/PR expression associates with non-response to HER2-targeted therapy (LR p=4.28E-08). Both HER2 and ER/PR signaling phenotypes are captured by BluePrint subtyping; and consistent with the individual pathway markers, tumors classified Luminal-type had a lower pCR rate relative to those classified as Her2-type (or Basal-type) (LR p=4.84E-11). These associations all retain significance in a model adjusting for HR status and treatment arm, and in the HR+HER2+ subset. In addition, we quantitatively assessed proliferation markers at the total protein (RPPA: Ki67), phospho-protein (pAURKA) and mRNA (proliferation signature Module11_Prolif) levels. All three proliferation biomarkers predict response overall; but this association is strongest within the HR+HER2+ subset (LR p=0.0012 (Module11_prolif), 0.0036 (pAURK), and 0.045 (Ki67)). None of the biomarkers tested were associated with response in the HR-HER2+ subset. Numbers are small within individual arms. Within the HR+HER2+ subtype, higher HER2 and lower ER/PR is observed in responders in all experimental arms; but the proliferation markers Module11_Prolif (LR p=0.0031) and Ki67 total protein (LR p=0.0029) are associated with response to TDM1/P but not H/P or N. Conclusion: High HER2 signaling at the expression, protein, and phospho-protein levels, and low ER signaling, all predict response to HER2-inhibition across treatment arms. Proliferation markers may be useful for prioritizing therapies in the HR+HER2+ subset. Citation Format: Denise M Wolf, Christina Yau, Julia Wulfkuhle, Lamorna Brown-Swigart, Smita M. Asare, Gillian L. Hirst, Laura Sit, Jane Perlmutter, I-SPY 2 TRIAL Consortium, Minetta Liu, John Park, Angela DeMichele, Douglas Yee, Don Berry, Laura Esserman, Emanuel Petricoin, Laura van t' Veer. HER2 signaling, ER, and proliferation biomarkers predict response to multiple HER2-targeted agents/combinations plus standard neoadjuvant therapy in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-02.

Purpose There is growing interest to enhance symptom monitoring during routine cancer care using patient-reported outcomes, but evidence of impact on clinical outcomes is limited. Methods We randomly assigned patients receiving routine outpatient chemotherapy for advanced solid tumors at Memorial Sloan Kettering Cancer Center to report 12 common symptoms via tablet computers or to receive usual care consisting of symptom monitoring at the discretion of clinicians. Those with home computers received weekly e-mail prompts to report between visits. Treating physicians received symptom printouts at visits, and nurses received e-mail alerts when participants reported severe or worsening symptoms. The primary outcome was change in health-related quality of life (HRQL) at 6 months compared with baseline, measured by the EuroQol EQ-5D Index. Secondary endpoints included emergency room (ER) visits, hospitalizations, and survival. Results Among 766 patients allocated, HRQL improved among more participants in the intervention group than usual care (34% v 18%) and worsened among fewer (38% v 53%; P < .001). Overall, mean HRQL declined by less in the intervention group than usual care (1.4- v 7.1-point drop; P < .001). Patients receiving intervention were less frequently admitted to the ER (34% v 41%; P = .02) or hospitalized (45% v 49%; P = .08) and remained on chemotherapy longer (mean, 8.2 v 6.3 months; P = .002). Although 75% of the intervention group was alive at 1 year, 69% with usual care survived the year (P = .05), with differences also seen in quality-adjusted survival (mean of 8.7 v. 8.0 months; P = .004). Benefits were greater for participants lacking prior computer experience. Most patients receiving intervention (63%) reported severe symptoms during the study. Nurses frequently initiated clinical actions in response to e-mail alerts. Conclusion Clinical benefits were associated with symptom self-reporting during cancer care.