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Abstract PS7-01: Characteristics and outcomes of SARS-CoV-2 infection in patients with invasive breast cancer (BC) from the COVID-19 and cancer consortium (CCC19) cohort study

2021· article· en· W3129720267 on OpenAlexaboutno aff
Ali Raza Khaki, Dimpy P. Shah, Maryam B. Lustberg, Melissa Accordino, Daniel G. Stover, Gayathri Nagaraj, Donna R. Rivera, Edith A. Perez, Sara M. Tolaney, Jeffrey Peppercorn, Petros Grivas, Jeremy L. Warner, Corrie Painter, Gilberto Lopes, Solange Peters, Michael A Thompson, Toni K. Choueiri, Brian I. Rini, Gary H. Lyman, Nicole M. Kuderer, Shaveta Vinayak

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerCancerCohortIntensive care unitProportional hazards modelLung cancerInternal medicineEmergency medicine

Abstract

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Abstract Background: Overall, patients with cancer experience a greater risk of adverse outcomes following SARS-CoV-2 infection; however, little is known for those with BC. Methods: CCC19 (NCT04354701) is an international cohort study aimed at investigating the impact of COVID-19 in patients with a history of or active cancer using de-identified data on patient demographics, cancer history, clinical course and outcomes of COVID-19. The current analysis includes patients from U.S. and Canada with invasive BC and laboratory-confirmed SARS-CoV-2 entered between March 17, 2020 and July 2, 2020. Co-primary outcomes were hospitalization during COVID-19 illness and 30-day all-cause mortality. Frequencies for categorical variables and medians (range) for continuous variables were estimated. Final presentation will include bivariable and multivariable Cox proportional hazards regression analysis to identify risk factors (including BC subtypes and therapies, for which data collection is ongoing) associated with 30-day all-cause mortality and severe COVID-19 illness (composite of any hospitalization requiring supplemental oxygen, admission to an intensive care unit [ICU], use of mechanical ventilation, or death). Results: During the study period, a total of 2683 patients with cancer and COVID-19 were accrued in the CCC19 registry including 529 (20%) with invasive BC. Among patients with BC, 352 (67%) were 60 years or older; 518 (98%) were women; 275 (52%) non-Hispanic White, 116 (22%) non-Hispanic Black, 70 (13%) Hispanic, 56 (11%) in other categorizations; 178 (34%) had a smoking history; 75 (14%) ECOG performance status ≥2; 191 (36%) with >2 active comorbidities; 64 (12%) with AJCC stage IV disease at BC diagnosis; and 267 (50%) were on anti-cancer treatment including systemic therapy, radiation, or surgery within 3 months of COVID-19 diagnosis. At least 323 (61%) patients with BC had 30-day follow-up after COVID-19 diagnosis, and 35 (7%) had 90-day follow-up. COVID-19 illness at initial diagnosis required outpatient care in 288 (54%), inpatient care in 193 (36%), and ICU care in 40 (8%). Overall, 247 (47%) were hospitalized and 30-day all-cause mortality was 9%. 30-day all-cause mortality rates by receipt of major BC treatment modalities (within past 3 months) were: 10% for those on cytotoxic systemic therapy vs 5% and 12% for noncytotoxic systemic therapy and local therapy, respectively. The table shows hospitalization and mortality outcomes by major demographic and BC treatment strata. The final presentation will incorporate the latest patient accrual and evaluate independent clinical risk factors associated with serious COVID-19 outcomes in patients with BC. Conclusions: This represents the largest study to date of COVID-19 outcomes in patients with invasive BC. Nearly half of the patients with BC required hospitalization during their COVID-19 disease course and we observed a 9% 30-day all-cause mortality. Submitted on behalf of the COVID-19 and Cancer Consortium (ccc19us.org) Table 1. COVID-19 related hospitalization and 30-day all-cause mortality for all patients with invasive BCNAny Hospitalization30-day all-cause MortalityN% [95% CI]N% [95% CI]Total population52924747 [42-51]499 [7-12]Age<601774425 [19-32]21 [0-4]60-691155144 [35-54]87 [3-13]70-791206655 [46-64]1714 [8-22]80+1178674 [65-81]2219 [12-27]ECOG PS0-132212238 [33-43]165 [3-8]2+756181 [71-89]1621 [13-32]Active Comorbidities0741014 [7-23]00 [0-5]1-22239442 [36-49]178 [5-12]>219112968 [60-74]2915 [10-21]Treatment IntentCurative1866434 [28-42]95 [2-9]Palliative743953 [41-64]1216 [9-27]Cancer StatusRemission/NED33115447 [41-52]247 [5-11]Active disease, stable or responding to treatment1194840 [31-50]76 [2-12]Active disease, progressing372773 [56-86]1130 [16-47]Treatment Modality (within 3 months)Cytotoxic chemotherapy833542 [31-54]810 [4-18]Noncytotoxic therapy1856435 [28-42]105 [3-10]Local therapy (surgery or radiation)341750 [32-68]412 [3-27] Citation Format: Ali Raza Khaki, Dimpy P Shah, Maryam B Lustberg, Melissa K Accordino, Daniel G Stover, Gayathri Nagaraj, Donna R Rivera, Edith A Perez, Sara M Tolaney, Jeffrey Peppercorn, Petros Grivas, Jeremy L Warner, Corrie A Painter, Gilberto de Lima Lopes, Jr, Solange Peters, Michael A Thompson, Toni K Choueiri, Brian I Rini, Gary H Lyman, Nicole M Kuderer, Shaveta Vinayak. Characteristics and outcomes of SARS-CoV-2 infection in patients with invasive breast cancer (BC) from the COVID-19 and cancer consortium (CCC19) cohort study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-01.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.156
GPT teacher head0.479
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2021
Admission routes1
Has abstractyes

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