Predictive factors for cancer treatment delay in an underserved urban population.

Authors

null

Risha Sheni

Albert Einstein College of Medicine, Bronx, NY

Risha Sheni , Jiyue Qin , Shankar Viswanathan , Enrico Castellucci , Vikas Mehta

Organizations

Albert Einstein College of Medicine, Bronx, NY, Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, Montefiore Medical Center and Albert Einstein College of Medicine, Bronx, NY, Department of Otorhinolaryngology, Head & Neck Surgery, Montefiore Medical Center, Bronx, NY

Research Funding

No funding received

Background: Incremental delays in cancer time to treatment initiation (TTI) have been shown to cause a proportional, independent increased risk of disease specific mortality for breast cancer, colorectal cancer (CRC), head and neck (HNC), non-small cell lung cancer (NSCLC) and pancreatic cancer. A portion of delays can be attributed to increasingly complex workup with modern imaging, genomic, and multidisciplinary/multimodality treatment paradigms. However, studies suggest delays are associated with racial and socioeconomic disparities, implicating a target for addressing inequitable care. Given Montefiore Medical Center (MMC) serves a racially diverse, socioeconomically challenged population, we sought to evaluate the association between patient factors and TTI to identify factors associated with TTI delay. Methods: Retrospective cohort study at an urban community-based academic center of patients diagnosed with or referred for curative intent treatment of breast cancer, CRC, HNC, NSCLC, and pancreatic cancer at MMC from January 2019 to December 2021. Variables of interest included tumor staging, primary treatment modality, marital status, Charlson Comorbidity Index (CCI) score, tobacco use, zip code, insurance type, language preference, primary care provider status, and inpatient (IP) admission or emergency room visit 30 days prior to diagnosis. Results: A total of 3430 patients (F=2376, M=1054) were identified (mean age 64.2 ± 13.3). Demographics are summarized in Table. The Median TTI was 21 days (7, 41 IQR). In assessing factors associated with TTI delay, patients who were IP 30 days before diagnosis were significantly more likely to have timely TTI for breast cancer (p<0.003), CRC (p<0.001), HNC (p<0.006), and NSCLC (p<0.001). For CRC, a higher CCI score was associated with TTI greater than 30 days (p<0.019). For lung cancer, older age (p<0.015) and having public insurance (p<0.001) were associated with TTI delay. Conclusions: IP admission 30 days before diagnosis was associated with timely TTI for breast cancer, CRC, HNC, and NSCLC. Other factors predictive of delay included CCI score in CRC, and advanced age at diagnosis and insurance type for NSCLC. This study identifies factors predicting delay and opportunities for addressing delay, thereby improving survival outcomes in our population.

Patient demographics, stratified by cancer type.


Breast
CRC
HNC
NSCLC
Pancreas
Number of Patients
1526 (44.5%)
624 (18.2%)
395 (11.5%)
628 (18.3%)
257 (7.5%)
Mean Age (SD)
61.5 (13.5)
65.3 (14.2)
64.3 (12.9)
68.2 (11.1)
68.2 (11.7)
Sex (M/F)
11 (0.7%)/

1515 (99.3%)
330 (52.9%)/

294 (47.1%)
270 (68.4%)/

125 (31.6%)
325 (51.8%)/ 303 (48.2%)
118 (45.9%)/

139 (54.1%)
Mean CCI Score (SD)
1.1 (0.4)
1.2 (0.5)
1.1 (0.4)
1.3 (0.6)
1.2 (0.5)
Delayed TTI* (>30 days)
675 (44.2%)
198 (31.7%)
154 (39.0%)
203 (32.3%)
47 (18.3%)

CCI, Charlson Comorbidity Index; TTI, Time to treatment initiation *TTI dichotomized – Using 30 days cutoff

Disclaimer

This material on this page is ©2024 American Society of Clinical Oncology, all rights reserved. Licensing available upon request. For more information, please contact licensing@asco.org

Abstract Details

Meeting

2022 ASCO Annual Meeting

Session Type

Publication Only

Session Title

Health Services Research and Quality Improvement

Track

Quality Care/Health Services Research

Sub Track

Quality Improvement

Citation

J Clin Oncol 40, 2022 (suppl 16; abstr e18608)

DOI

10.1200/JCO.2022.40.16_suppl.e18608

Abstract #

e18608

Abstract Disclosures