Abstract P4-12-12: Assessing the impact of the COVID-19 pandemic on cancer treatment decision-making and care experiences
Bibliographic record
Abstract
Abstract BACKGROUND: While the COVID-19 pandemic has reshaped how oncology is practiced, we sought to understand itseffects on treatment decision-making and care experiences amongst cancer patients at the Tom BakerCancer Centre in Calgary, Canada. METHODS: A 24 item, cross-sectional survey was developed based on literature review and iterative feedback fromoncology physicians, nurses, and a patient advisor. Survey domains included fear of COVID-19 andperceived risk, uptake of COVID-19 public health measures, cancer treatment decision-making duringthe pandemic, and cancer care experiences during the pandemic. Demographic, cancer and treatment-related information was obtained from the electronic medical record for patients who consented andcompleted the survey. In the first quarter of 2021, 161 patients accrued including 44 breast cancerpatients. The cohort characteristics and survey responses were summarized using descriptive statistics. RESULTS: For the 44 participants with breast cancer, all were female and the median age was 59 years (range 35-83 years). Our breast cancer cohort was almost evenly split between those with stage I-III (45.5%) andthose with metastatic disease (54.5%). Time since diagnosis was as follows: less than 1 year (17patients), 1-3 years (10 patients), 3-5 years (5 patients), and more than 5 years (9 patients). Treatmentsreceived since declaration of the pandemic included: surgery (21 patients), radiation (17 patients),chemotherapy (25 patients), endocrine therapy (25 patients), and other systemic therapies such as boneand anti-HER2 agents (15 patients). Just over half of the participants (54.5%) agreed or strongly agreedthat they were at increased risk of contracting COVID19; however, fewer patients expressed beinguncomfortable thinking about COVID-19 (45.4%), afraid of COVID-19 (38.6%), or fearful of dying fromCOVID19 (31.8%). The vast majority (>93%) of patients followed public health recommendations formitigating the risk of contracting COVID-19 (i.e. masking, frequent hand washing/sanitization, and socialdistancing) and 70.4% expressed a willingness to receive the vaccine when available. Of therespondents, 19 had undergone testing for COVID-19 at least once and 3 tested positive. Only 2 patientsreported that their surgical course was altered due to the pandemic and no patients declinedtreatments or perceived delays or modifications in therapies otherwise. Of 25 breast participants whohad experienced a cancer-related telehealth appointment during the pandemic, 21 (84%) agreed orstrongly agreed with being satisfied with the encounter. CONCLUSION: The COVID-19 pandemic caused minimal perceived disruption to care amongst a small cohort of breastcancer patients being treated at our centre. While experience with a cancer-related telehealthappointment was not universal, our findings support acceptability of its use. Citation Format: Noura Alsafar, Desiree Hao, Nimira Alimohamed, Sunil Samnani, Sasha Lupichuk. Assessing the impact of the COVID-19 pandemic on cancer treatment decision-making and care experiences [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 P4-12-12.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".