ABSTRACT
Background and Aims
The COVID‐19 pandemic led to delayed treatment for pancreatic ductal adenocarcinoma (PDAC) and other cancers due to factors such as lockdown protocols, social distancing practices, and prioritization of emergency procedures. Demographic factors create disparities in pancreatic cancer care access, further impacting time to treatment. Prolonged time to treatment initiation has been associated with worse health outcomes for patients with solid tumor malignancies, particularly PDAC. Communities at higher risk of PDAC were disproportionately affected by the pandemic due to factors including residence in healthcare deserts, inadequate insurance, and low health literacy. This study aims to investigate whether racial disparities in time to treatment for PDAC were exacerbated during the COVID‐19 pandemic, with particular attention to vulnerable populations.
Methods
National Cancer Database (NCDB) data were utilized to identify patients diagnosed with PDAC between 2018 and 2020. Patients were categorized as either “pre‐COVID” (2018) or “post‐COVID” (2020). A two‐way ANOVA and post hoc testing were conducted with time to treatment as the primary dependent variable.
Results
A statistically significant relationship was identified between race and time to treatment (F = 7.16, p < 0.001). Post hoc tests revealed significant differences (p < 0.001) between White and Black patients, with Black patients experiencing greater delays both before and after COVID‐19. The interaction between time of diagnosis and race had a statistically significant impact on time to treatment (F = 1.68, p = 0.03), indicating that certain races experienced greater delays than others. Chinese patients experienced the most significant increase in time to treatment, with an average delay extending by 7.8 days from 2018 to 2020 (p = 0.046).
Conclusion
The analysis revealed significant relationships between race, time of diagnosis, and time to treatment, with Chinese patients experiencing the most substantial increase in treatment delay during the pandemic. These findings demonstrate how COVID‐19 disruptions intensified preexisting healthcare inequities and highlight the need to address demographic disparities in healthcare access.
1. Background
The COVID‐19 pandemic resulted in significant delays in both cancer diagnosis and treatment owing to many factors, including lockdown protocols and fear of hospital‐acquired COVID [1]. The consequences of these delays are significant and far‐reaching. Prolonged time to treatment initiation (TTI) has been associated with worse health outcomes for patients with solid tumor malignancies, including pancreatic adenocarcinoma (PDAC) [2]. PDAC is considered one of the most lethal cancers, with a 12.5% 5‐year survival rate [3]. Given its high mortality, treatment delays can significantly impact disease prognosis. A study by Khorana and colleagues revealed that a 6‐week delay in TTI was associated with a 9% absolute increase in Stage I pancreatic cancer mortality [2]. Thus, timely treatment is essential to achieving optimal clinical outcomes.
These findings are particularly relevant given the demographic variations in incidence. From 2001 to 2015, the incidence of pancreatic cancer was significantly higher for Black patients compared to White patients (24.7 vs. 19.4 per 100,000). Conversely, between 2000 and 2020, Asian patients had lower pancreatic cancer mortality (75.2/million) compared to Black (134.0/million) and White patients (107.8/million) [4]. The increased incidence and mortality among Black patients should be met with improved access to care. However, Black patients receive less treatment and fewer surgical procedures for resectable cancer compared to White patients with a comparable stage of PDAC [5]. These disparities were further exacerbated during the COVID‐19 pandemic owing to several factors, including limited insurance coverage, inadequate social policies and programs, increased poverty and homelessness, and lower health literacy [6, 7]. These inequities reflect broader patterns of structural racism in healthcare policy that have historically limited access to care for racial and ethnic minority populations [8].
The combined effects of increased disease incidence among specific demographic cohorts and reduced access to care during the pandemic warrant investigation given their epidemiological implications. The purpose of this study was to examine the influence of the pandemic on time to treatment for PDAC in patients of various races.
2. Methods
National Cancer Database (NCDB) data [9] were utilized to identify patients diagnosed with PDAC (histology code 8140, indicating adenocarcinoma, and behavior code 3, indicating malignant behavior), resulting in a cohort of 35,840 patients. Once eligible patients were identified from the NCDB database, they were further characterized by race and year of diagnosis. Patients diagnosed with PDAC in 2018 were categorized as “pre‐COVID,” while those diagnosed in 2020 were categorized as “post‐COVID.” As such, 18,196 patients were classified under the pre‐COVID category, while 17,644 patients were classified under the post‐COVID category. Data from 2019 were excluded due to considerable variability in patient care during this inflection point, which could have introduced significant skew in the results. Instead, 2018 and 2020 were selected as reliable proxies for pre‐ versus post‐pandemic analyses. This method of chronological classification aligns with prior literature, including a retrospective study assessing the effect of the COVID‐19 pandemic on 1‐year cancer survival in the United States [10].
The cohort included 29,160 White patients (81.4%), 4623 Black patients (12.9%), and 2057 patients (5.7%) of other racial groups including Asian, Hispanic, Native American, and other/unknown race. Due to small sample sizes in individual racial subcategories, focused analyses examined White, Black, and Chinese patients, who had sufficient numbers for statistical comparison.
Race codes were assigned per the NCDB data dictionary. Statistical analyses were performed using IBM Statistical Package for Social Sciences (SPSS version 29). A two‐way analysis of variance (ANOVA) was conducted with time to treatment as the primary dependent variable and race and time of diagnosis (pre‐COVID vs. post‐COVID) as independent variables. Tukey's post hoc tests were performed for pairwise comparisons. All tests were two‐sided with statistical significance defined as p < 0.05. This NCDB variable was defined as the number of days between the date of initial diagnosis and the date of the first course of treatment (surgery, radiation, systemic therapy including chemotherapy, hormone therapy, immunotherapy, hematologic transplant/endocrine procedures, or other therapy).
This study utilized de‐identified data from the NCDB and was deemed exempt from institutional review board approval as it does not constitute human subjects research per 45 CFR 46.101(b)(4).
3. Results
The two‐way ANOVA revealed a statistically significant relationship between race and time to treatment (F = 7.16, p < 0.001; Table 1). This finding indicated a statistically significant relationship between an individual's race and the time elapsed for the patient to receive treatment for PDAC after diagnosis. Consistent with findings from previous research, Tukey's post hoc tests revealed a statistically significant difference (p < 0.001) in time to treatment between White and Black patients, with Black patients experiencing greater time to treatment both before and after COVID‐19 (Table 2). In 2018, White patients received first treatment a mean of 31.8 days after initial diagnosis, while Black patients received first treatment 37.9 days after diagnosis, reflecting a significant difference of 6.1 days (p < 0.001). Similarly, in 2020, White patients received first treatment 32.2 days after diagnosis and Black patients received first treatment 35.5 days after diagnosis, resulting in a statistically significant 3.3‐day difference (p < 0.001). Thus, both pre‐ and post‐COVID, race had an association with time to treatment, with Black patients experiencing delayed treatment for PDAC compared to their White counterparts.
Table 1.
Two‐way ANOVA results for time to treatment in PDAC.
| Effect | F‐statistic | p |
|---|---|---|
| Race | 7.16 | < 0.001 |
| Time of diagnosis (pre‐ vs. post‐COVID) | NS | NS |
| Race × time of diagnosis | 1.68 | 0.033 |
Table 2.
Pre‐ versus post‐COVID time to treatment comparisons for White versus Black patients.
| Year | White (days) | Black (days) | Difference (days) | p |
|---|---|---|---|---|
| 2018 | 31.8 | 37.9 | 6.1 | < 0.001 |
| 2020 | 32.2 | 35.5 | 3.3 | < 0.001 |
Further analysis revealed that the differences in time to treatment did not vary significantly between 2018 and 2020 for White and Black patients overall, indicating that the pandemic did not substantially alter the existing racial disparities in treatment delays between these groups. On average, White patients received treatment for PDAC around 4.7 days earlier than Black patients, with minimal differences between pre‐ and post‐COVID cohorts.
Examination of temporal changes showed that White patients experienced minimal change in time to treatment between 2018 and 2020 (31.8 vs. 32.2 days), while Black patients showed a slight decrease (37.9 vs. 35.5 days). In contrast, Chinese patients had the shortest time to treatment in 2018 (30.3 days), comparable to or better than both White and Black patients. However, by 2020, Chinese patients experienced a substantial delay (38.1 days), exceeding White patients (32.2 days) and approaching the delays experienced by Black patients (35.5 days).
Further analysis of the interaction between race and time of diagnosis revealed a statistically significant impact on time to treatment (F = 1.68, p = 0.03; Table 1), suggesting that certain racial groups experienced greater delays in time to treatment during the pandemic. Notably, pairwise comparisons revealed that, compared to White and Black patients, patients of Chinese origin experienced the most significant increase in time to treatment for PDAC, with an average delay increasing by 7.8 days from 2018 to 2020 (p = 0.046; Table 3). Specifically, the mean time to treatment for patients of Chinese origin was 30.3 days in 2018, rising to 38.1 days in 2020. This 7.8‐day increase represents the most substantial temporal change observed among the racial groups examined. Contextualizing how this finding may translate to patient outcomes is key to determining clinical significance. One observational study found that each additional week of delay in treatment for pancreatic cancer correlated with a 1.2%–3.2% absolute increase in mortality risk [2]. Therefore, the delays experienced by Chinese patients may have adversely affected mortality.
Table 3.
Pre‐ versus post‐COVID time to treatment comparison for Chinese patients.
| Year | Mean time to treatment (days) | Pairwise comparison | |
|---|---|---|---|
| Difference (days) | p | ||
| 2018 | 30.3 | 7.8 | 0.046 |
| 2020 | 38.1 | ||
4. Discussion
Our analysis reveals a significant relationship between race, time of diagnosis (pre‐ vs. post‐COVID), and time to treatment for PDAC—one of the most lethal malignancies worldwide. Although Black patients consistently faced prolonged treatment delays both before and after the pandemic, patients of Chinese origin experienced the most pronounced increase in time to treatment during the post‐COVID era. These findings demonstrate how COVID‐19‐related disruptions intensified preexisting healthcare inequities, highlighting the roles of structural racism, discrimination, and limited access to care. These findings are consistent with evidence that anti‐Asian sentiment during the pandemic created barriers to timely treatment [11].
Our results demonstrate the need for comprehensive interventions, including policy reforms and community‐based outreach, tailored to historically marginalized racial groups. Future research should examine the interplay between social determinants of health and clinical outcomes to identify strategies for reducing these disparities. Addressing these inequities is essential to ensure equitable access to timely treatment for all patients with PDAC.
Author Contributions
Archana Venkatesan: conceptualization, methodology, data curation, formal analysis, writing – original draft, writing – review and editing. Raag Patel: formal analysis, writing – review and editing. Shawn M. Doss: visualization, writing – review and editing. Kat Light: writing – review and editing. Ashley Lomax: writing – review and editing. Danny Yakoub: writing – review and editing, supervision. All authors have read and approved the final version of the manuscript. Archana Venkatesan had full access to all of the data in this study and takes complete responsibility for the integrity of the data and the accuracy of the data analysis.
Funding
The authors received no specific funding for this work.
Disclosure
The lead author Archana Venkatesan affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.
Conflicts of Interest
The authors declare no conflicts of interest.
Data Availability Statement
The authors have nothing to report.
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Associated Data
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Data Availability Statement
The authors have nothing to report.