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Background:Oncologists often order genomic testing to inform treatment for worsening cancer. The resulting correlation between genomic testing timing and prognosis, or “informative entry,” can bias observational clinico-genomic research. The efficacy of existing approaches to this problem in clinico-genomic cohorts is poorly understood.Methods:We simulated clinico-genomic cohorts followed from an index date to death. Subgroups in each cohort who underwent genomic testing before death were “observed.” We varied data generation parameters under four scenarios: (i) independent testing and survival times; (ii) correlated testing and survival times for all patients; (iii) correlated testing and survival times for a subset of patients; and (iv) testing and mortality exclusively following progression events. We examined the behavior of conditional Kendall tau (Tc) statistics, Cox entry time coefficients, and biases in overall survival (OS) estimation and biomarker inference across scenarios.Results:Scenario #1 yielded null Tc and Cox entry time coefficients and unbiased OS inference. Scenario #2 yielded positive Tc, negative Cox entry time coefficients, underestimated OS, and biomarker associations biased toward the null. Scenario #3 yielded negative Tc, positive Cox entry time coefficients, and underestimated OS, but biomarker estimates were less biased. Scenario #4 yielded null Tc and Cox entry time coefficients, underestimated OS, and biased biomarker estimates. Transformation and copula modeling did not provide unbiased results.Conclusions:Approaches to informative clinico-genomic cohort entry, including Tc and Cox entry time statistics, are sensitive to heterogeneity in genotyping and survival time distributions.Impact:Novel methods are needed for unbiased inference using observational clinico-genomic data.

INTRODUCTION: Electronic health record (EHR) discontinuity (missing out-of-network encounters) can lead to information bias. We sought to construct an algorithm that identifies high EHR-continuity among oncology patients. METHODS: Using a linked Medicare-EHR database and regression, we sought to 1) measure how often Medicare claims for outpatient encounters were substantiated by visits recorded in the EHR, and 2) predict continuity ratio, defined as the yearly proportion of outpatient encounters reported to Medicare that were captured by EHR data. The prediction model’s performance was evaluated with the coefficient of determination and Spearman’s correlation. We quantified variable misclassification by decile of continuity ratio using standardized difference and sensitivity. RESULTS: A total of 79,678 subjects met all eligibility criteria. Predicted and observed continuity was highly correlated (σ(Spearman) = 0.86). On average across all variables measured, MSD was reduced by a factor of 1/7(th) and sensitivity was improved 35-fold comparing subjects in the highest vs. lowest decile of CR. CONCLUSION: In the oncology population, restricting EHR-based study cohorts to subjects with high continuity may reduce misclassification without greatly impacting representativeness. Further work is needed to elucidate the best manner of implementing continuity prediction rules in cohort studies.

PURPOSE: Oncology electronic health record (EHR) databases have increased in quality and availability over the past decade, yet it remains unclear whether these clinical practice data can be used to conduct reliable comparative effectiveness studies. We sought to emulate a clinical trial with EHR data in the advanced breast cancer population and compare our results against the trial. METHODS: This cohort study used EHR data from US oncology practices. All elements of the study were defined to mimic the PALOMA-2 trial as closely as possible. Patients with hormone-positive, HER-2 negative metastatic breast cancer with no prior treatment for metastatic disease were included. Patients initiating palbociclib and letrozole on the same day following the earliest record of metastasis were compared to those initiating letrozole only. The primary associational measure was the conditional hazard ratio for time-to-next treatment (TTNT). TTNT is well-measured in our data source and amenable for calibration against the randomized study results of the PALOMA-2 trial. We used multiple imputation for several patient characteristics with missing values. RESULTS: There were 3836 study-eligible women with advanced breast cancer. The hazard ratio for TTNT in the observational study (HR: 0.62; 95% CI: 0.56–0.68) was closely aligned with that of the randomized trial (HR: 0.64; 95% CI: 0.52–0.78). CONCLUSIONS: Under our assumptions on missing data and comparability of the two study populations, results from our non-randomized study closely matched that of the randomized trial. Further studies are needed to determine whether EHR data can yield reliable conclusions on treatment effects in oncology.

PURPOSE: The COVID-19 pandemic forced rapid adoption of telemedicine (TM) for breast oncology visits in the United States, but the appropriate role of postpandemic TM is uncertain. We sought to understand physician and advance practice practitioner perspectives on the use of TM for outpatient breast cancer care through an electronically administered survey. METHODS: Breast medical oncology clinicians at two academic cancer centers and five satellite locations affiliated with the Dana Farber Cancer Institute and the Massachusetts General Cancer Center were invited to respond to a 21-question survey administered in September 2021 about clinicians' perceptions and attitudes toward TM during the previous 12 months. RESULTS: Of the 71 survey invitations, 51 clinicians (36 physicians and 15 advance practice practitioners) provided survey responses (response rate = 72%). Ninety-two percent of respondents (n = 47) agreed that TM visits enhance patient care. Ninety-two percent of respondents (n = 46) also agreed that TM is valuable for early-stage breast cancer follow-up visits. Most respondents felt that there was no difference between TM and face-to-face (F2F) visits when it came to patient adherence, ease of ordering tests, ease of accessing patient records, and workflow outside of the visit (82%, 82%, 78%, and 53%, respectively). Fifty-one percent of respondents (n = 26) said that TM was better for timely access to follow-up appointments. Most respondents said that F2F visits were better for seeing physical problems, personal connection with patients, overall quality of visits, and patient-physician communication (100%, 75%, 65%, and 63%, respectively). CONCLUSION: Breast clinicians believe that TM is a valuable tool to enhance outpatient breast cancer care. TM was felt to be appropriate for routine follow-up visits and second opinion consultations and is as good as or better than F2F visits for several routine aspects of breast cancer care.

Background Guidelines for follow-up after locoregional breast cancer treatment recommend imaging for distant metastases only in the presence of patient signs and/or symptoms. However, guidelines have not been updated to reflect advances in imaging, systemic therapy, or the understanding of biological subtype. We assessed the association between mode of distant recurrence detection and survival. Methods In this observational study, a stage-stratified random sample of women with stage II-III breast cancer in 2006-2007 and followed through 2016 was selected, including up to 10 women from each of 1217 Commission on Cancer facilities (n = 10 076). The explanatory variable was mode of recurrence detection (asymptomatic imaging vs signs and/or symptoms). The outcome was time from initial cancer diagnosis to death. Registrars abstracted scan type, intent (cancer-related vs not, asymptomatic surveillance vs not), and recurrence. Data were merged with each patient’s National Cancer Database record. Results Surveillance imaging detected 23.3% (284 of 1220) of distant recurrences (76.7%, 936 of 1220 by signs and/or symptoms). Based on propensity-weighted multivariable Cox proportional hazards models, patients with asymptomatic imaging compared with sign and/or symptom detected recurrences had a lower risk of death if estrogen receptor (ER) and progesterone receptor (PR) negative, HER2 negative (triple negative; hazard ratio [HR] = 0.73, 95% confidence interval [CI] = 0.54 to 0.99), or HER2 positive (HR = 0.51, 95% CI = 0.33 to 0.80). No association was observed for ER- or PR-positive, HER2-negative (HR = 1.14, 95% CI = 0.91 to 1.44) cancers. Conclusions Recurrence detection by asymptomatic imaging compared with signs and/or symptoms was associated with lower risk of death for triple-negative and HER2-positive, but not ER- or PR-positive, HER2-negative cancers. A randomized trial is warranted to evaluate imaging surveillance for metastases results in these subgroups.

The National Cancer Institute Division of Cancer Control and Population Science hosted a virtual conference on the Future of Cancer Health Economics Research and included a presentation from a workgroup that considered current challenges and future directions in health economics research centered on cancer treatment. The workgroup identified 3 broad categories of focus: data limitations, opportunities for training for clinicians and health economists interested in collaboration, and the need for prospective economic study of cancer treatment. Within these areas of focus, the workgroup recommended the following: improvement of the availability of key economic measures in data available to researchers, creation of more comprehensive datasets robust to insurance type or coverage, development of cancer care health economics research-focused symposia, instituting clear mechanisms to support integration of economic analyses alongside clinical trials, development of standardized methods to measure the cost of cancer care to health-care systems and patients, and development of standardized evaluations that include measures of social determinants of health.

Persons living with advanced cancer have intensive symptoms and psychosocial needs that often result in visits to the Emergency Department (ED). We report on program engagement, advance care planning (ACP), and hospice use for a 6-month longitudinal nurse-led, telephonic palliative care intervention for patients with advanced cancer as part of a larger randomized trial. Patients 50 years and older with metastatic solid tumors were recruited from 18 EDs and randomized to receive nursing calls focused on ACP, symptom management, and care coordination or specialty outpatient palliative care (ClinicialTrials.gov: NCT03325985). One hundred and five (50%) graduated from the 6-month program, 54 (26%) died or enrolled in hospice, 40 (19%) were lost to follow-up, and 19 (9%) withdrew prior to program completion. In a Cox proportional hazard regression, withdrawn subjects were more likely to be white and have a low symptom burden compared to those who did not withdraw. Two hundred eighteen persons living with advanced cancer were enrolled in the nursing arm, and 182 of those (83%) completed some ACP. Of the subjects who died, 43/54 (80%) enrolled in hospice. Our program demonstrated high rates of engagement, ACP, and hospice enrollment. Enrolling subjects with a high symptom burden may result in even greater program engagement.

Supplemental Methods. Supplemental Table 1: ââ,¬â€¹Genomic Data Characterization by Center. Supplemental Table 2: ââ,¬â€¹Gene Panels Submitted by Each Center. Figure S1: Number of putative germline SNPs per sample, before and after uniform germline filtering. Figure S2ââ,¬â€¹. Distribution of total somatic mutation burden per sample stratified by sequencing panel. Figure S3: ââ,¬â€¹Log-scale comparison of mutation frequencies at hotspot sites between GENIE (data aggregated from all sequencing panels) and cancerhotspots.org (CHS) using a binomial test. Figure S4:ââ,¬â€¹ Comparison of mutation frequencies at hotspot sites in each GENIE sequencing panel with cancerhotspots.org (CHS) using a binomial test.

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AACR GENIE Data Guide

Supplementary Tables and Figures

We conducted next-generation DNA sequencing on 335 biliary tract cancers and characterized the genomic landscape by anatomic site within the biliary tree. In addition to frequent FGFR2 fusions among patients with intrahepatic cholangiocarcinoma (IHCC), we identified FGFR2 extracellular domain in-frame deletions (EID) in 5 of 178 (2.8%) patients with IHCC, including two patients with FGFR2 p.H167_N173del. Expression of this FGFR2 EID in NIH3T3 cells resulted in constitutive FGFR2 activation, oncogenic transformation, and sensitivity to FGFR inhibitors. Three patients with FGFR2 EIDs were treated with Debio 1347, an oral FGFR1/2/3 inhibitor, and all showed partial responses. One patient developed an acquired L618F FGFR2 kinase domain mutation at disease progression and experienced a further partial response for 17 months to an irreversible FGFR2 inhibitor, futibatinib. Together, these findings reveal FGFR2 EIDs as an alternative mechanism of FGFR2 activation in IHCC that predicts sensitivity to FGFR inhibitors in the clinic.Significance:FGFR2 EIDs are transforming genomic alterations that occur predominantly in patients with IHCC. These FGFR2 EIDs are sensitive to FGFR inhibition in vitro, and patients with these alterations benefited from treatment with FGFR inhibitors in the clinic.This article is highlighted in the In This Issue feature, p. 2355

AKT inhibitors have promising activity in AKT1E17K-mutant estrogen receptor (ER)–positive metastatic breast cancer, but the natural history of this rare genomic subtype remains unknown. Utilizing AACR Project GENIE, an international clinicogenomic data-sharing consortium, we conducted a comparative analysis of clinical outcomes of patients with matched AKT1E17K-mutant (n = 153) and AKT1–wild-type (n = 302) metastatic breast cancer. AKT1-mutant cases had similar adjusted overall survival (OS) compared with AKT1–wild-type controls (median OS, 24.1 vs. 29.9, respectively; P = 0.98). AKT1-mutant cases enjoyed longer durations on mTOR inhibitor therapy, an observation previously unrecognized in pivotal clinical trials due to the rarity of this alteration. Other baseline clinicopathologic features, as well as durations on other classes of therapy, were broadly similar. In summary, we demonstrate the feasibility of using a novel and publicly accessible clincogenomic registry to define outcomes in a rare genomically defined cancer subtype, an approach with broad applicability to precision oncology.Significance:We delineate the natural history of a rare genomically distinct cancer, AKT1E17K-mutant ER-positive breast cancer, using a publicly accessible registry of real-world patient data, thereby illustrating the potential to inform drug registration through synthetic control data.See related commentary by Castellanos and Baxi, p. 490.

Background: In 2017, DNA mismatch repair/microsatellite instability (MMR/MSI) testing was nationally recommended for advanced colorectal cancers based on favorable immune checkpoint inhibitor responses among patients with MMR-deficient/MSI-high tumors. Methods: Patients ages ≥20-years-old presenting with stage IV colorectal adenocarcinoma from 2010 to 2017 were identified from the National Cancer Database. 2017 was the latest year with available testing utilization data. Patient, tumor, socioeconomic, and care setting characteristics were evaluated for association with upfront MMR/MSI testing in 2017 using multivariable logistic regression and average adjusted predicted probabilities (%AAP). Results: Among 72,830 stage IV colorectal cancers, upfront MMR/MSI testing levels increased from 16.4% in 2010 to 56.4% in 2017. For patients diagnosed in 2017 (i.e., following national recommendations, n = 10,022), testing levels were lower for older patients (Padj < 0.001), and were independent of patients' race/ethnicity and insurance status. Patients from the poorest quartile of households received less testing [49.6%AAP, 99.9% confidence interval (CI) 45.5–53.7] than patients from the 3rd (56.9%AAP, 99.9% CI, 53.3–60.6; Padj < 0.001) or 4th quartiles (57.6%AAP, 99.9% CI, 54.3–60.9; Padj < 0.001). Although testing levels improved most at community programs, they remained lower in 2017 (46.6%AAP, 99.9% CI, 41.0–52.1) compared with academic/NCI-designated comprehensive cancer centers (62.8%AAP, 99.9% CI, 59.7–65.8; Padj < 0.001). Conclusions: Upfront MMR/MSI testing utilization for patients with advanced colorectal cancer has increased but there is still substantial need for optimization. Testing utilization disproportionately lagged for patients who were older, from the poorest quartile of households, or managed at community cancer programs. Impact: Our findings indicate opportunities for improving rates of MMR/MSI testing and reporting, possibly through incorporation into quality control and accreditation metrics.

Adjuvant chemotherapy is not recommended for patients with average-risk stage II (T3N0) colon cancer. Nevertheless, a subgroup of these patients who are CDX2-negative might benefit from adjuvant chemotherapy. We evaluated the cost-effectiveness of testing for the absence of CDX2 expression followed by adjuvant chemotherapy (fluorouracil combined with oxaliplatin [FOLFOX]) for patients with stage II colon cancer.We developed a decision model to simulate a hypothetical cohort of 65-year-old patients with average-risk stage II colon cancer with 7.2% of these patients being CDX2-negative under 2 different interventions: (1) test for the absence of CDX2 expression followed by adjuvant chemotherapy for CDX2-negative patients and (2) no CDX2 testing and no adjuvant chemotherapy for any patient. We derived disease progression parameters, adjuvant chemotherapy effectiveness and utilities from published analyses, and cancer care costs from the Surveillance, Epidemiology, and End Results (SEER)-Medicare data. Sensitivity analyses were conducted.Testing for CDX2 followed by FOLFOX for CDX2-negative patients had an incremental cost-effectiveness ratio of $5500/quality-adjusted life-years (QALYs) compared with no CDX2 testing and no FOLFOX (6.874 vs 6.838 discounted QALYs and $89 991 vs $89 797 discounted US dollar lifetime costs). In sensitivity analyses, considering a cost-effectiveness threshold of $100 000/QALY, testing for CDX2 followed by FOLFOX on CDX2-negative patients remains cost-effective for hazard ratios of0.975 of the effectiveness of FOLFOX in CDX2-negative patients in reducing the rate of developing a metastatic recurrence.Testing tumors of patients with stage II colon cancer for CDX2 and administration of adjuvant treatment to the subgroup found CDX2-negative is a cost-effective and high-value management strategy across a broad range of plausible assumptions.

Background Combination irinotecan and cetuximab is approved for irinotecan-refractory metastatic colorectal cancer (mCRC). It is unknown if adding bevacizumab improves outcomes. Patients and Methods In this multicenter, randomized, double-blind, placebo-controlled phase II trial, patients with irinotecan-refractory RAS-wildtype mCRC and no prior anti-EGFR therapy were randomized to cetuximab 500 mg/m2, bevacizumab 5 mg/kg, and irinotecan 180 mg/m2 (or previously tolerated dose) (CBI) versus cetuximab, irinotecan, and placebo (CI) every 2 weeks until disease progression or intolerable toxicity. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS), objective response rate (ORR), and adverse events (AEs). Results The study closed early after the accrual of 36 out of a planned 120 patients due to changes in funding. Nineteen patients were randomized to CBI and 17 to CI. Baseline characteristics were similar between arms. Median PFS was 9.7 versus 5.5 months for CBI and CI, respectively (1-sided log-rank P = .38; adjusted hazard ratio [HR] = 0.64; 95% confidence interval [CI], 0.25-1.66). Median OS was 19.7 versus 10.2 months for CBI and CI (1-sided log-rank P = .02; adjusted HR = 0.41; 95% CI, 0.15-1.09). ORR was 36.8% for CBI versus 11.8% for CI (P = .13). Grade 3 or higher AEs occurred in 47% of patients receiving CBI versus 35% for CI (P = .46). Conclusion In this prematurely discontinued trial, there was no significant difference in the primary endpoint of PFS between CBI and CI. There was a statistically significant improvement in OS in favor of CBI compared with CI. Further investigation of CBI for the treatment of irinotecan-refractory mCRC is warranted. Clinical Trial Registration: NCT02292758

Background: Clinician-rated adverse event data from pivotal trials of the CDK4/6 inhibitor palbociclib (palbo) in patients (pts) with HR+ HER2- metastatic breast cancer (MBC) describe fatigue as a common non-hematologic toxicity. While palbo and endocrine therapy (ET) significantly improve outcomes compared to ET alone, in a pooled analysis of the PALOMA trials, rates of incident Common Terminology Criteria for Adverse Events (CTCAE) all-grade fatigue over 4.2 years of treatment approached 39.2%, with grade 3/4 at 2.5%. As these studies included only provider-rated CTCAE toxicity, it is important to quantify pts’ ratings of fatigue severity, which may differ from clinician assessments. Methods: Eligible pts with HR+ HER2- MBC, initiating standard-dose palbo with ET (aromatase inhibitor or fulvestrant), and without clinically meaningful fatigue prior to initiation of palbo, were followed for the 6 initial treatment cycles. The absence of baseline fatigue was established using the patient-reported Functional Assessment of Chronic Illness Therapy Fatigue Scale (FACIT-F), a 13-item scale (range 0-52, lower score = more fatigue) validated against anemia to indicate clinically meaningful fatigue if FACIT-F score =34; PRO-CTCAE fatigue severity grade 3/4 vs. Citation Format: Shadab A Rahman, Erica L Mayer, Hanneke Poort, Deborah Schrag, Stephanie C Tung, Eric S Zhou, Aleta Wiley, Lauren Finkelstein, Elkhansaa Elguenaoui, Moira Nolan, Hadine Joffe. Incidence of patient-reported fatigue developing in patients receiving palbociclib and endocrine therapy for advanced HR+ HER2- breast cancer [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 P4-09-01.

Purpose:We wanted to determine the prognosis and the phenotypic characteristics of hormone receptor–positive advanced breast cancer tumors harboring an ERBB2 mutation in the absence of a HER2 amplification.Experimental Design:We retrospectively collected information from the American Association of Cancer Research-Genomics Evidence Neoplasia Information Exchange registry database from patients with hormone receptor–positive, HER2-negative, ERBB2-mutated advanced breast cancer. Phenotypic and co-mutational features, as well as response to treatment and outcome were compared with matched control cases ERBB2 wild type.Results:A total of 45 ERBB2-mutant cases were identified for 90 matched controls. The presence of an ERBB2 mutation was not associated with worse outcome determined by overall survival (OS) from first metastatic relapse. No significant differences were observed in phenotypic characteristics apart from higher lobular infiltrating subtype in the ERBB2-mutated group. ERBB2 mutation did not seem to have an impact in response to treatment or time-to-progression (TTP) to endocrine therapy compared with ERBB2 wild type. In the co-mutational analyses, CDH1 mutation was more frequent in the ERBB2-mutated group (FDR < 1). Although not significant, fewer co-occurring ESR1 mutations and more KRAS mutations were identified in the ERBB2-mutated group.Conclusions:ERBB2-activating mutation was not associated with a worse OS from time of first metastatic relapse, or differences in TTP on treatment as compared with a series of matched controls. Although not significant, differences in coexisting mutations (CDH1, ESR1, and KRAS) were noted between the ERBB2-mutated and the control group.

Supplementary Figure from Natural History and Characteristics of ERBB2-mutated Hormone Receptor–positive Metastatic Breast Cancer: A Multi-institutional Retrospective Case–control Study from AACR Project GENIE

Supplementary Table from Natural History and Characteristics of ERBB2-mutated Hormone Receptor–positive Metastatic Breast Cancer: A Multi-institutional Retrospective Case–control Study from AACR Project GENIE

When a standardized diagnostic test fails to locate the primary site of a metastatic cancer, it is diagnosed as a cancer of unknown primary (CUP). CUPs account for 3-5% of all cancers but do not have established targeted therapies, leading to typically dismal outcomes. Here, we develop OncoNPC, a machine learning classifier of CUP, trained on targeted next generation sequencing data from 34,567 tumors across 22 primary cancer types collected as part of routine clinical care at three institutions under AACR Project GENIE initiative [1]. OncoNPC achieved a weighted F1 score of 0.94 for high confidence predictions on known cancer types (65% of held-out samples). To evaluate its clinical utility, we applied OncoNPC to 971 CUP tumor samples from patients treated at the Dana-Farber Cancer Institute (DFCI). OncoNPC CUP subtypes exhibited significantly different survival outcomes, and identified potentially actionable molecular alterations in 23% of tumors. Importantly, patients with CUP, who received first palliative intent treatments concordant with their OncoNPC predicted sites, showed significantly better outcomes (Hazard Ratio 0.348, 95% C.I. 0.210 - 0.570, p-value 2.32×10−5) after accounting for potential measured confounders. As validation, we showed that OncoNPC CUP subtypes exhibited significantly higher polygenic germline risk for the predicted cancer type. OncoNPC thus provides evidence of distinct CUP subtypes and offers the potential for clinical decision support for managing patients with CUP.

PURPOSE With the growing number of available targeted therapeutics and molecular biomarkers, the optimal care of patients with cancer now depends on a comprehensive understanding of the rapidly evolving landscape of precision oncology, which can be challenging for oncologists to navigate alone. METHODS We developed and implemented a precision oncology decision support system, GI TARGET, (Gastrointestinal Treatment Assistance Regarding Genomic Evaluation of Tumors) within the Gastrointestinal Cancer Center at the Dana-Farber Cancer Institute. With a multidisciplinary team, we systematically reviewed tumor molecular profiling for GI tumors and provided molecularly informed clinical recommendations, which included identifying appropriate clinical trials aided by the computational matching platform MatchMiner, suggesting targeted therapy options on or off the US Food and Drug Administration–approved label, and consideration of additional or orthogonal molecular testing. RESULTS We reviewed genomic data and provided clinical recommendations for 506 patients with GI cancer who underwent tumor molecular profiling between January and June 2019 and determined follow-up using the electronic health record. Summary reports were provided to 19 medical oncologists for patients with colorectal (n = 198, 39%), pancreatic (n = 124, 24%), esophagogastric (n = 67, 13%), biliary (n = 40, 8%), and other GI cancers. We recommended ≥ 1 precision medicine clinical trial for 80% (406 of 506) of patients, leading to 24 enrollments. We recommended on-label and off-label targeted therapies for 6% (28 of 506) and 25% (125 of 506) of patients, respectively. Recommendations for additional or orthogonal testing were made for 42% (211 of 506) of patients. CONCLUSION The integration of precision medicine in routine cancer care through a dedicated multidisciplinary molecular tumor board is scalable and sustainable, and implementation of precision oncology recommendations has clinical utility for patients with cancer.

PURPOSE To inform precision oncology, methods are needed to use electronic health records (EHRs) to identify patients with cancer who are experiencing clinical inflection points, consistent with worsening prognosis or a high propensity to change treatment, at specific time points. Such patients might benefit from real-time screening for clinical trials. METHODS Using serial unstructured imaging reports for patients with solid tumors or lymphoma participating in a single-institution precision medicine study, we trained a deep neural network natural language processing (NLP) model to dynamically predict patients' prognoses and propensity to start new palliative-intent systemic therapy within 30 days. Model performance was evaluated using Harrell's c-index (for prognosis) and the area under the receiver operating characteristic curve (AUC; for new treatment and new clinical trial enrollment). Associations between model outputs and manual annotations of cancer progression were also evaluated using the AUC. RESULTS A deep NLP model was trained and evaluated using 302,688 imaging reports for 16,780 patients. In a held-out test set of 34,770 reports for 1,952 additional patients, the model predicted survival with a c-index of 0.76 and initiation of new treatment with an AUC of 0.77. Model-generated prognostic scores were associated with annotation of cancer progression on the basis of manual EHR review (n = 1,488 reports for 110 patients with lung or colorectal cancer) with an AUC of 0.78, and predictions of new treatment were associated with annotation of cancer progression on the basis of manual EHR review with an AUC of 0.84. CONCLUSION Training a deep NLP model to identify clinical inflection points among patients with cancer is feasible. This approach could identify patients who may benefit from real-time targeted clinical trial screening interventions at health system scale.

David Merola,1,2 Jessica Young,2,3 Deborah Schrag,4 Kueiyu Joshua Lin,1,2,5 Nicholas Robert,6 Sebastian Schneeweiss1,2 1Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA; 2Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA; 3Department of Population Medicine, Harvard Medical School & Harvard Pilgrim Healthcare Institute, Boston, MA, USA; 4Department of Medicine, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical School New York, New York, NY, USA; 5Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; 6Ontada, Irving, TX, USACorrespondence: David Merola, Email davemerola@gmail.comBackground: The use of electronic health records (EHR) data to assess drug effectiveness in clinical oncology practice is of great interest to regulators, clinicians, and payers. However, the utility of EHR data in clinical effectiveness studies may be limited by missing data, unmeasured confounding, and imperfect outcome surveillance. This study sought to emulate and compare the results of a randomized controlled trial investigating the efficacy of palbociclib with fulvestrant vs letrozole in advanced breast cancer.Methods: This was a cohort study using longitudinal EHR data derived from outpatient oncology practices in the United States. Eligibility criteria from the PARSIFAL trial were emulated as closely as possible. Patients were included if they had hormone-positive, human epidermal growth factor receptor – 2 (HER-2) negative metastatic breast cancer and had no record of prior treatment for metastatic disease. Patients initiating first-line treatment with palbociclib and fulvestrant following their first record of metastasis were compared to those initiating palbociclib and letrozole on the same day. Treatments were ascertained by oncology medication ordering records in the data source. The primary outcome was death as recorded in the oncologists’ EHR systems.Results: There were 1886 eligible women in the study cohort. Although the 3-year survival was meaningfully lower in clinical practice (59%) compared to the randomized trial (78%), the relative effect size was a hazard ratio (HR) of 1.07 (95% CI: 0.86– 1.35), similar to the randomized trial (HR = 1.00; 95% CI: 0.68– 1.48).Conclusion: Despite common challenges encountered in EHR-based studies, it is possible to achieve similar conclusions to emulated randomized trials with the application of analytic approaches that address missing data, confounding, and selection bias. This is a promising finding in light of other emulations and ongoing efforts to improve data from clinical practice and causal analytics.Keywords: real-world evidence, comparative effectiveness research, oncology, pharmacoepidemiology, healthcare databases

ImportanceThe risk of recurrence in patients with locally advanced rectal cancer has historically been determined after surgery, relying on pathologic variables. A growing number of patients are being treated without surgery, and their risk of recurrence needs to be calculated differently.ObjectiveTo develop a dynamic calculator for estimating the probability of recurrence-free survival (RFS) in patients with rectal cancer who undergo total neoadjuvant therapy (TNT) (induction systemic chemotherapy and chemoradiotherapy) and either surgery or watch-and-wait management.Design, Setting, and ParticipantsThis cohort study included patients who presented with stage II or III rectal cancer between June 1, 2009, and March 1, 2015, at a comprehensive cancer center. Conditional modeling was incorporated into a previously validated clinical calculator to allow the probability of RFS to be updated based on whether the patient remained in watch-and-wait management or underwent delayed surgery. Data were analyzed from November 2021 to March 2022.ExposureTNT followed by immediate surgery or watch-and-wait management with the possibility of delayed surgery.Main Outcomes and MeasuresRFS, concordance index, calibration curves.ResultsOf the 302 patients in the cohort, 204 (68%) underwent surgery within 3 months from TNT completion (median [range] age, 51 [22-82] years; 78 [38%] women), 54 (18%) underwent surgery more than 3 months from TNT completion (ie, delayed surgery; median [range] age, 62 [31-87] years; 30 [56%] female), and 44 (14%) remained in watch-and-wait management as of April 21, 2021 (median [range] age, 58 [32-89] years; 16 [36%] women). Among patients who initially opted for watch-and-wait management, migration to surgery due to regrowth or patient choice occurred mostly within the first year following completion of TNT, and RFS did not differ significantly whether surgery was performed 3.0 to 5.9 months (73%; 95% CI, 52%-92%) vs 6.0 to 11.9 months (71%; 95% CI, 51%-99%) vs more than 12.0 months (70%; 95% CI, 49%-100%) from TNT completion (P = .70). RFS for patients in the watch-and-wait cohort at 12 months from completion of TNT more closely resembled patients who had undergone surgery and had a pathologic complete response than the watch-and-wait cohort at 3 months from completion of TNT. Accordingly, model performance improved over time, and the concordance index increased from 0.62 (95% CI, 0.53-0.71) at 3 months after TNT to 0.66 (95% CI, 0-0.75) at 12 months.Conclusions and RelevanceIn this cohort study of patients with rectal cancer, the clinical calculator reliably estimated the likelihood of RFS for patients who underwent surgery immediately after TNT, patients who underwent delayed surgery after entering watch-and-wait management, and patients who remained in watch-and-wait management. Delayed surgery following attempted watch-and-wait did not appear to compromise oncologic outcomes. The risk calculator provided conditional survival estimates at any time during surveillance and could help physicians counsel patients with rectal cancer about the consequences of alternative treatment pathways and thereby support informed decisions that incorporate patients’ preferences.

Often electronic tools are built with English proficient (EP) patients in mind. Cancer patients with limited English proficiency (LEP) experience gaps in care and are at risk for excess toxic effects if they are unable to effectively communicate with their care team.To evaluate whether electronic patient-reported outcome tools (ePROs) built to improve health outcomes for EP patients might also be acceptable for LEP patients in the context of oral cancer-directed therapies (OCDT).This qualitative study was conducted at a single National Cancer Institute-designated comprehensive cancer center. In 2019, English-speaking and Spanish-speaking LEP patients with cancer receiving oral chemotherapies were recruited to participate in a qualitative focus group examining patient attitudes toward ePROs and electronic tools that are used to manage adherence and symptoms related to oral therapies. Six focus groups were held for EP patients and 1 for Spanish-speaking LEP patients. LEP was defined as patients who self-identified as needing an interpreter to navigate the health care system. Data analysis was performed April through June of 2019.Enrolled patients participated in a focus group lasting approximately 90 minutes.The perspectives of patients with cancer treated with oral chemotherapies on integrating ePROs into their care management.Among the 46 participants included in the study, 46 (100%) were White, 10 (22%) were Latinx Spanish-speaking, 43 (93%) were female, and 37 (80%) were aged at least 50 years or older. Among the 6 focus groups with 6 to 8 EP patients (ranging from 6 to 8 participants) and 1 focus group with 10 Spanish-speaking LEP patients, this qualitative study found that EP and LEP patients had different levels of acceptability of using technology and ePRO tools to manage their OCDT. EP patients felt generally positive toward OCDT and were not generally interested in using electronic tools to manage their care. LEP patients generally disliked OCDT and welcomed the use of technology for health management, particularly when addressing gaps in symptom management by their oncology clinicians.Although most electronic interventions target EP patients, these findings reveal the willingness of LEP patients to participate in technology-based interventions. Expanding ePROs to LEP patients may help to manage gaps in communication about treatment and potential adverse events because of the willingness of LEP patients to use ePRO tools to manage their health. This qualitative assessment is a strategic step in determining the resources needed to narrow the digital health gap and extend the value of PROs to the LEP oncology population.

Although not without controversy, readmission is entrenched as a hospital quality metric with statistical analyses generally based on fitting a logistic-Normal generalized linear mixed model. Such analyses, however, ignore death as a competing risk, although doing so for clinical conditions with high mortality can have profound effects; a hospital’s seemingly good performance for readmission may be an artifact of it having poor performance for mortality. in this paper we propose novel multivariate hospital-level performance measures for readmission and mortality that derive from framing the analysis as one of cluster-correlated semi-competing risks data. We also consider a number of profiling-related goals, including the identification of extreme performers and a bivariate classification of whether the hospital has higher-/lower-than-expected readmission and mortality rates via a Bayesian decision-theoretic approach that characterizes hospitals on the basis of minimizing the posterior expected loss for an appropriate loss function. in some settings, particularly if the number of hospitals is large, the computational burden may be prohibitive. To resolve this, we propose a series of analysis strategies that will be useful in practice. Throughout, the methods are illustrated with data from CMS on N = 17,685 patients diagnosed with pancreatic cancer between 2000–2012 at one of J = 264 hospitals in California.

Anticancer therapy changes tumor physiology and genomics, making it a key variable in cancer studies. Although antineoplastics given at a single institution may be available in research-ready format, treatment at external institutions prior to receiving care at academic medical centers, common among patients at these centers, is often only described in free-text clinical notes, necessitating manual curation for downstream analysis. To overcome this bottleneck, we trained and validated natural language processing (NLP) models using initial consult notes to identify whether patients had received treatment at external institutions and studied the impact of these putative treatments on tumor genomics. Training data were derived from the AACR Project GENIE Biopharma Collaborative (BPC) for 2,663 patients at Memorial Sloan Kettering (MSK) across four cancer types. For each patient, we selected initial visits with medical and radiation oncologists based on an a priori note prioritization scheme and determined “ground-truth” prior external medications based on manually curated BPC administration records, whitelisting MSK-given medications. We trained logistic regression and clinical longformer models to identify external treatment receipt and evaluated model performance with 5-fold cross-validation. The clinical longformer model performed best across evaluation metrics, with an average area under the receiver operating characteristic curve of 0.972, macro-averaged precision/recall of 0.854/0.902 and macro-averaged F1 score of 0.876. Re-review of discrepant cases suggested that 75% of “false positives” may be due to curation error. We used our model to infer treatment status in a pan-cancer cohort with tumor genomic profiling using our institutional sequencing platform. Out of 48,447 patients, 11,900 were predicted to have received external treatment. Patients with putative external treatment had higher alteration frequencies in resistance-related genes than untreated patients and comparable to known pre-treated patients, including ESR1 in patients with breast cancer, AR in patients with prostate cancer, and EGFR T790M in patients with EGFR-mutated non-small cell lung cancer. Patients with putative external treatments, similar to known pre-treated patients, had shorter survival compared to treatment-naïve patients of the same cancer type. NLP can abstract external treatment status from clinical notes. When applied at scale, our model could help mitigate confounding variables and identify relationships between clinicogenomic variables and anticancer therapy. Citation Format: Thinh N. Tran, Karl B. Pichotta, Si-Yang Liu, Christopher Fong, Anisha Luthra, Brooke Mastrogiacomo, Steven Maron, Deborah Schrag, Sohrab P. Shah, Pedram Razavi, Bob T. Li, Gregory J. Riely, Nikolaus Schultz, Justin Jee. Identification of anti-neoplastic therapy given before initial visit at a referral center using natural language processing applied to medical oncology initial consultation notes. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4259.

IMPORTANCE: Electronic systems that facilitate patient-reported outcome (PRO) surveys for patients with cancer may detect symptoms early and prompt clinicians to intervene. OBJECTIVE: To evaluate whether electronic symptom monitoring during cancer treatment confers benefits on quality-of-life outcomes. DESIGN, SETTING, AND PARTICIPANTS: Report of secondary outcomes from the PRO-TECT (Alliance AFT-39) cluster randomized trial in 52 US community oncology practices randomized to electronic symptom monitoring with PRO surveys or usual care. Between October 2017 and March 2020, 1191 adults being treated for metastatic cancer were enrolled, with last follow-up on May 17, 2021. INTERVENTIONS: In the PRO group, participants (n = 593) were asked to complete weekly surveys via an internet-based or automated telephone system for up to 1 year. Severe or worsening symptoms triggered care team alerts. The control group (n = 598) received usual care. MAIN OUTCOMES AND MEASURES: The 3 prespecified secondary outcomes were physical function, symptom control, and health-related quality of life (HRQOL) at 3 months, measured by the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30; range, 0-100 points; minimum clinically important difference [MCID], 2-7 for physical function; no MCID defined for symptom control or HRQOL). Results on the primary outcome, overall survival, are not yet available. RESULTS: Among 52 practices, 1191 patients were included (mean age, 62.2 years; 694 [58.3%] women); 1066 (89.5%) completed 3-month follow-up. Compared with usual care, mean changes on the QLQ-C30 from baseline to 3 months were significantly improved in the PRO group for physical function (PRO, from 74.27 to 75.81 points; control, from 73.54 to 72.61 points; mean difference, 2.47 [95% CI, 0.41-4.53]; P = .02), symptom control (PRO, from 77.67 to 80.03 points; control, from 76.75 to 76.55 points; mean difference, 2.56 [95% CI, 0.95-4.17]; P = .002), and HRQOL (PRO, from 78.11 to 80.03 points; control, from 77.00 to 76.50 points; mean difference, 2.43 [95% CI, 0.90-3.96]; P = .002). Patients in the PRO group had significantly greater odds of experiencing clinically meaningful benefits vs usual care for physical function (7.7% more with improvements of ≥5 points and 6.1% fewer with worsening of ≥5 points; odds ratio [OR], 1.35 [95% CI, 1.08-1.70]; P = .009), symptom control (8.6% and 7.5%, respectively; OR, 1.50 [95% CI, 1.15-1.95]; P = .003), and HRQOL (8.5% and 4.9%, respectively; OR, 1.41 [95% CI, 1.10-1.81]; P = .006). CONCLUSIONS AND RELEVANCE: In this report of secondary outcomes from a randomized clinical trial of adults receiving cancer treatment, use of weekly electronic PRO surveys to monitor symptoms, compared with usual care, resulted in statistically significant improvements in physical function, symptom control, and HRQOL at 3 months, with mean improvements of approximately 2.5 points on a 0- to 100-point scale. These findings should be interpreted provisionally pending results of the primary outcome of overall survival. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03249090

PURPOSE Collecting patient-reported outcomes (PROs) can improve symptom control and quality of life, enhance doctor-patient communication, and reduce acute care needs for patients with cancer. Digital solutions facilitate PRO collection, but without robust electronic health record (EHR) integration, effective deployment can be hampered by low patient and clinician engagement and high development and deployment costs. The important components of digital PRO platforms have been defined, but procedures for implementing integrated solutions are not readily available. METHODS As part of the NCI's IMPACT consortium, six health care systems partnered with Epic to develop an EHR-integrated, PRO-based electronic symptom management program (eSyM) to optimize postoperative recovery and well-being during chemotherapy. The agile development process incorporated user-centered design principles that required engagement from patients, clinicians, and health care systems. Whenever possible, the system used validated content from the public domain and took advantage of existing EHR capabilities to automate processes. RESULTS eSyM includes symptom surveys on the basis of the PRO-Common Terminology Criteria for Adverse Events (PRO-CTCAE) plus two global wellness questions; reminders and symptom self-management tip sheets for patients; alerts and symptom reports for clinicians; and population management dashboards. EHR dependencies include a secure Health Insurance Portability and Accountability Act-compliant patient portal; diagnosis, procedure and chemotherapy treatment plan data; registries that identify and track target populations; and the ability to create reminders, alerts, reports, dashboards, and charting shortcuts. CONCLUSION eSyM incorporates validated content and leverages existing EHR capabilities. Build challenges include the innate technical limitations of the EHR, the constrained availability of site technical resources, and sites' heterogenous EHR configurations and policies. Integration of PRO-based symptom management programs into the EHR could help overcome adoption barriers, consolidate clinical workflows, and foster scalability and sustainability. We intend to make eSyM available to all Epic users.

Immune checkpoint inhibitors (ICIs) have yielded remarkable responses in patients across multiple cancer types, but often lead to immune related adverse events (irAEs). Although a germline cause for irAEs has been hypothesized, no systematic genome wide association study (GWAS) has been performed and no individual variants associated with the overall likelihood of developing irAEs have yet been identified. We carried out a Genome-Wide Association Study (GWAS) of 1,751 patients on ICIs across 12 cancer types, with replication in an independent cohort of 196 patients and independent clinical trial data from 2275 patients. We investigated two irAE phenotypes: (i) high-grade (3-5) events defined through manual curation and (ii) all detectable events (including high-grade) defined through electronic health record (EHR) diagnosis followed by manual confirmation. We identified three genome-wide significant associations (p−8) in the discovery cohort associated with all-grade irAEs: rs16906115 near IL7 (combined p=1.6×10−11; hazard ratio (HR)=2.1), rs75824728 near IL22RA1 (combined p=6.6×10−9; HR=1.9), and rs113861051 on 4p15 (combined p=1.3×10−8, HR=2.0); with rs16906115 replicating in two independent studies. The association near IL7 colocalized with the gain of a novel cryptic exon for IL7, a critical regulator of lymphocyte homeostasis. Patients carrying the IL7 germline variant exhibited significantly increased lymphocyte stability after ICI initiation than non-carriers, and this stability was predictive of downstream irAEs and improved survival.

Immune checkpoint inhibitors (ICIs) have yielded remarkable responses but often lead to immune-related adverse events (irAEs). Although germline causes for irAEs have been hypothesized, no individual variant associated with developing irAEs has been identified. We carried out a genome-wide association study of 1,751 patients on ICIs across 12 cancer types. We investigated two irAE phenotypes: (1) high-grade (3-5) and (2) all-grade events. We identified 3 genome-wide significant associations (P 5 × 10

PURPOSE The American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative is a multi-institution effort to build a pan-cancer repository of genomic and clinical data curated from the electronic health record. For the research community to be confident that data extracted from electronic health record text are reliable, transparency of the approach used to ensure data quality is essential. MATERIALS AND METHODS Four institutions participating in AACR's Project GENIE created an observational cohort of patients with cancer for whom tumor molecular profiling data, therapeutic exposures, and treatment outcomes are available and will be shared publicly with the research community. A comprehensive approach to quality assurance included assessments of (1) feasibility of the curation model through pressure test cases; (2) accuracy through programmatic queries and comparison with source data; and (3) reproducibility via double curation and code review. RESULTS Assessments of feasibility resulted in critical modifications to the curation directives. Queries and comparison with source data identified errors that were rectified via data correction and curator retraining. Assessment of intercurator reliability indicated a reliable curation model. CONCLUSION The transparent quality assurance processes for the GENIE BPC data ensure that the data can be used for analyses that support clinical decision making and advances in precision oncology.

Importance Real-world data sets that combine clinical and genomic data may be subject to left truncation (when potential study participants are not included because they have already passed the milestone of interest at the time of study recruitment). The lapse between diagnosis and molecular testing can present analytic challenges and threaten the validity and interpretation of survival analyses. Observations Effects of ignoring left truncation when estimating overall survival are illustrated using data from the American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative (GENIE BPC), and a straightforward risk-set adjustment approach is described. Ignoring left truncation results in overestimation of overall survival: unadjusted median survival estimates from diagnosis among patients with stage IV non-small cell lung cancer or stage IV colorectal cancer were overestimated by more than 1 year. Conclusions and relevance Clinicogenomic data are a valuable resource for evaluation of real-world cancer outcomes and should be analyzed using appropriate methods to maximize their potential. Analysts must become adept at application of appropriate statistical methods to ensure valid, meaningful, and generalizable research findings.

Introduction. Medicare’s Oncology Care Model (OCM) was a demonstration project that tied performance-based payments to cost and quality goals for participating oncology practices. A major concern about OCM regarded inclusion of high-cost cancer therapies which could potentially disincentivize oncologists from prescribing novel therapies and could exacerbate racial disparities in access to novel cancer technologies. Methods: This retrospective cohort study used SEER-Medicare data to identify patients who were eligible to receive one of 10 novel cancer therapies that received FDA approval in the 18 months leading up to implementation of OCM. The difference-in-differences cohort analysis matched patients treated by OCM-participating oncologists to non-OCM-participating oncologists and used a multivariable mixed effects regression model to evaluate whether OCM participation changed the likelihood that patients received novel therapies versus alternative treatments. A pre-planned triple difference-in-difference-in-differences analysis evaluated the impact of OCM on Black/White racial disparities in receipt of novel therapies. Results. The study included 2,839 matched patients (760 OCM, 2,079 non-OCM) who had a median age of 73 years and were 56% female, 85% White, 8% Black and 94% non-Hispanic. Among non-OCM patients, 33.2% and 39.9% received novel therapies before and after the start of OCM, respectively, vs 40.1% and 50.3% for OCM patients (adjusted difference-in-differences: 3.5 percentage points [95% CI -3.7 – 10.7 percentage points, p=0.34]). Overall, Black patients were 39% less likely to receive novel therapies compared to White patients (OR 0.61, 95% CI 0.42-0.89, p Citation Format: Christopher R. Manz, Angela C. Tramontano, Hajime Uno, Ravi B. Parikh, Justin E. Bekelman, Deborah Schrag. Evaluation of the effect of Medicare’s Oncology Care Model on racial disparities in patient receipt of novel cancer therapies [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A050.

The immune checkpoint inhibitor (ICI) pembrolizumab is US FDA approved for treatment of solid tumors with high tumor mutational burden (TMB-high; ≥10 variants/Mb). However, the extent to which TMB-high generalizes as an accurate biomarker in diverse patient populations is largely unknown. Using two clinical cohorts, we investigated the interplay between genetic ancestry, TMB, and tumor-only versus tumor-normal paired sequencing in solid tumors. TMB estimates from tumor-only panels substantially overclassified individuals into the clinically important TMB-high group due to germline contamination, and this bias was particularly pronounced in patients with Asian/African ancestry. Among patients with non-small cell lung cancer treated with ICIs, those misclassified as TMB-high from tumor-only panels did not associate with improved outcomes. TMB-high was significantly associated with improved outcomes only in European ancestries and merits validation in non-European ancestry populations. Ancestry-aware tumor-only TMB calibration and ancestry-diverse biomarker studies are critical to ensure that existing disparities are not exacerbated in precision medicine.

243 Background: Patients (pts) undergoing surgery for suspected malignancy may experience burdensome post-operative symptoms which can compromise outcomes and necessitate acute care. In prior randomized controlled trials at academic medical centers, patient-reported outcome (PRO)-based symptom management solutions improved clinical outcomes. Attempts to generalize this approach to real-world surgical pts have been challenged by perceptions that severe symptoms rarely occur, responding to severe symptoms can be burdensome, and uncertainty about which symptoms are likely to be severe and need interventions. Methods: Six US-based healthcare systems deployed eSyM, an EHR-integrated symptom management program. Pts undergoing surgery for suspected or confirmed thoracic (THOR), gastrointestinal (GI), and gynecologic (GYN) malignancies received automated questionnaires via MyChart portal 1-3 times weekly for up to 3 months after discharge. Questionnaires based on the PRO-CTCAE included 10 required and 20 optional symptoms, all scored as 0 (no symptoms), 1 (mild), 2 (moderate), or 3 (severe). Additional questions assessed functional status, overall wellbeing, wound discharge, and wound redness. Frequency and predictors of severe reporting were assessed using descriptive statistics and logistic regression modeling. Results: 21,012 surgical eSyM questionnaires were submitted between October 2019 - March 2022 by 3,781 unique pts (median age 63 years, 66.9% female, 92.1% white, 57.9% married, and 37.5% retired). 17% of questionnaires (16% of GI, 14% of GYN, and 21% of THOR) included at least 1 severe symptom. Frequencies of severe symptom reporting appear in Table with physical function impairment, general pain, and fatigue as the top three. Severe symptoms were more likely to be reported by younger, female, or unemployed pts(p < 0.01). In comparison to GI pts, GYN pts reported fewer and THOR pts reported more severe symptoms (p < 0.03). Conclusions: A meaningful minority of pts reported severe symptoms, suggesting that symptom monitoring could benefit pts without over-taxing clinicians. There were few strong patient-level predictors of severe symptoms, arguing that population surveillance may be preferable to targeted surveillance. Interventions are needed to address common severe symptoms and future studies should define most effective mitigation strategies for these symptoms. Clinical trial information: NCT03850912. [Table: see text]