Abstract PS2-27: Benefits of a rapid diagnostic centre for breast cancer care during the COVID-19 pandemic
Bibliographic record
Abstract
Abstract BACKGROUND: Changes in access to breast imaging and suspension of mammographic screening during the COVID-19 pandemic had the potential to significantly delay breast cancer diagnostic pathways. The Gattuso Rapid Diagnostic Centre (GRDC) is an innovative clinic that provides a patient-centered approach for investigation of suspicious breast abnormalities and sees approximately 1200 patients per year. The aim of this study was to assess the impact of the pandemic on patient volumes and imaging at this high-volume breast rapid diagnostic centre. METHODS: A retrospective review of consecutive patients who presented to the GRDC from the start of the pandemic (March 12, 2020) until May 31, 2020 was performed. The number of patients, reason for referral, cancer detection rate (CDR), and waiting time from appointment to diagnosis were evaluated and compared to a corresponding time period in 2019. RESULTS: A total of 168 new patients presented to the GRDC during the study period, corresponding to a 32.3% decrease in the number of patients compared to 2019 (n=248). Seventy-eight patients (46.4%) were referred due to the presence of a clinical palpable abnormality, which represented an increase of 13.8% (n=81 [32.7%] in 2019; p=0.005). Out of 168 patients, 69 were diagnosed with a breast malignancy, yielding a CDR of 41.1% during the pandemic versus 111 patients in 2019 (CDR of 44.8%; p= 0.456). The average time from appointment at GRDC to diagnosis was lower at 0.76 days vs 1.21 days in 2019. The rate of same day diagnosis was significantly higher at 39.5% vs 27.0% in 2019 (p=0.008). Twenty-five patients (14.9%) received neoadjuvant systemic therapy compared to 16 patients (6.5%) in 2019 (p=0.005). CONCLUSION: There were fewer patients presenting for breast investigations during the pandemic period and a significant increase in the percentage of patients with palpable masses as the cause for referral with no appreciable change in the CDR. The presence of a rapid diagnostic breast center enabled patients with concerning breast symptoms to access and receive expedited assessment. This ensured patients did not undergo diagnostic delays despite the health care restrictions that emerged during the COVID-19 pandemic. Citation Format: Gary Ko, Sharmy Sarvanantham, Sangita Sequeira, Vrutika Prajapati, David R. McCready, Vivianne Freitas, Tulin D. Cil. Benefits of a rapid diagnostic centre for breast cancer care during the COVID-19 pandemic [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 PS2-27.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".