Effects of treatment delays on outcomes in pancreatic adenocarcinoma

Introduction

Pancreatic cancer remains one of the deadliest gastrointestinal malignancies in the United States. Despite advancements in diagnostics with endoscopic ultrasound and evolving treatments, it continues to carry a strikingly poor prognosis, with a 5-year mortality of 88% (1-3). Over 95% of pancreatic cancers are pancreatic ductal adenocarcinomas (PDAC), which are predicted to become the second leading cause of cancer-related death by 2030, with the median survival for metastatic disease of only 12 months (4-6).

Given the overall poor prognosis of pancreatic adenocarcinoma, significant emphasis has been placed on time for diagnosis and treatment. A recent retrospective analysis estimated the median time from symptom onset to diagnosis to be around 32 days, with time from diagnosis to treatment around 18 days (7). Other studies have reported ranges from diagnosis to treatment between 3 to 12 weeks (8,9). Patients with early stage [1–3] disease should be referred for multidisciplinary management and consideration of curative surgical resection (10,11). Moreover, a crucial distinction, independent of clinical stage, is resectability, as neo-adjuvant chemotherapy may allow patients with borderline resectable disease at presentation to become surgical candidates. Unfortunately, more than 80% of patients are found to have unresectable disease at presentation, for which palliative chemotherapy is the current standard of care.

Despite recent investigations, it remains unclear how delays in diagnosis and treatment impact mortality. We aim to comprehensively assess the effect of treatment delays on initial therapy and outcomes in patients with PDAC.

Methods

The November 2022 submission of the Surveillance, Epidemiology, and End Results (SEER) Database Program provided by the National Cancer Institute (NCI) was queried for primary pancreatic adenocarcinoma from 2010–2020 following approval by our institutional IRB. The SEER Program is an ongoing, contract-supported program via NCI with population-based cancer incidence data along with individual patient, treatment and tumor characteristics from U.S. cancer registries (http://www.seer.cancer.gov). SEER currently publishes cancer data from population-based registries covering approximately 48% of the US population. It is the only comprehensive source of population-based information in the United States that includes stage of cancer at the time of diagnosis and patient survival data (12).

The International Classification of Diseases for Oncology 3rd Edition (ICD-O-3) expanded revision codes from SEER, produced in collaboration with the North American Association of Central Cancer Registries (NAACCR), were used to identify cases of pancreatic malignancy. An adapted classification scheme from the tumors of adolescents and young adults (AYA) schema was used to subsequently identify cases of pancreatic adenocarcinoma using code 9.3.9.2. Patients with previous primary or multiple primary tumors were excluded. Tumors from 2010–2015, 2016–2017, and 2018–2020 were staged using the “Derived American Joint Committee on Cancer (AJCC) Stage Group, 7^th edition”, “Derived SEER Combined Stage Group (2016–2017)”, and “Derived Evidence of Disease 2018 Stage Group (2018+)” variables provided in SEER, respectively. Other demographic and tumor data including age at diagnosis, sex, race, tumor size, tumor grade (well differentiated, moderately differentiated, poorly differentiated), radiation therapy (yes, no/unknown), chemotherapy (yes, no), and year of diagnosis were also collected. A patient’s median household income (MHI) was obtained through the “median household income inflation adjusted to 2021 variable”.

Initial treatment information was determined using surgical codes provided by SEER “RX Summ—Surg Prim Site (1998+)”. Pancreaticoduodenectomy (Whipple) was inclusive of “partial pancreatectomy and duodenectomy”, “partial pancreatectomy and duodenectomy w/o partial gastrectomy”, “partial pancreatectomy and duodenectomy w/partial gastrectomy”, and “extended pancreaticoduodenectomy”. Distal pancreatectomy consisted of “distal pancreatectomy, NOS”. Total pancreatectomy consisted of “total pancreatectomy” and “total pancreatectomy and partial gastrectomy or duodenectomy”. Pancreatectomy, NOS consisted of “pancreatectomy NOS”.

Time from diagnosis to treatment was determined using the integer variable “months from diagnosis to treatment” provided in SEER. As designated on seer.cancer.gov, “treatment could include surgery, radiation therapy, chemotherapy, hormone, immunotherapy, and/or active surveillance” (13). For the purposes of PDAC therapy, treatment includes surgery, chemotherapy, and/or immunotherapy. The greater than 1-month group was inclusive of patients receiving treatment at 1 month or greater. The less than 1-month group did not include patients who received treatment at 1 month. The months from diagnosis to treatment variable is left blank by SEER if any of the date components in the formula are missing or if the calculated value >24 months (14). Overall mortality (OM), cancer-specific mortality (CSM), and non-cancer related mortality (NCM) were defined based on accepted definitions (15,16). Survival and follow-up time in months is provided by SEER and are validated measurements created using complete dates, including days, using a standardized algorithm to minimize variability from data collected from different cancer registries (17). Follow-up time was calculated from the date of diagnosis. Patients with incomplete follow-up or treatment data were excluded from survival analyses.

Stratified survival analyses were assessed using the Kaplan-Meier method, and clinical significance between curves was determined via the log-rank (Mantel-Cox) test. The data that support the findings of this study are openly available in https://seer.cancer.gov/.

Statistical analysis

Statistical analyses and figure production were performed using R studio (R version 3.6.1, Boston, MA, USA). Between-group comparisons were conducted via t-test for parametric continuous variables, Mann-Whitney U-test for non-parametric continuous variables, and chi-squared testing for categorical variables. All statistical tests were two-sided using P values ≤0.05 to determine statistical significance.

Multivariable Cox proportional hazards regression models were performed to determine hazard ratios (HR) for variables associated with OM. A non-automated, forward selection method of variables trending toward significance (alpha level <0.2) was used to determine the variables included in the multivariate analysis. The regression model was right-censored to account for patients who were alive at time of their last follow-up. There were no variables with missingness >10% used in regression. Univariate regression HRs were labeled “crude”, and multivariate HRs were labeled “adjusted”. Appropriateness of fit of the multivariable model was ensured by maintaining a concordance greater than 0.65. Avoidance of multicollinearity between independent variables was ensured by maintaining a variance inflation factor of <1.5 for all variables.

Ethical consideration

The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study’s ethical approval was exempted by the institutional ethics board of The University of Virginia and individual consent for this retrospective analysis was waived.

Results

Demographic analysis

A total of 64,382 patients with a primary pancreatic adenocarcinoma diagnosed between 2010 and 2020 were included in the demographic analysis (Table 1). A total of 18,673 (29%) patients underwent initial therapy within 1 month of diagnosis (early), and 45,709 (71%) patients underwent initial therapy 1 month after diagnosis (delayed). Patients who received treatment after 1 month were on average older (67.28 vs. 66.27 years), and less likely to be White (68.8% vs. 69.9%), and more likely to be Black (11.2% vs. 10%). There were no significant differences in distribution of household income by time to treatment (TTT) group. The proportion of patients receiving treatment within 1 month of diagnosis decreased over the study period with 34%, 28.6%, and 24.5% receiving treatment within 1 month of diagnosis from 2010–2013, 2014–2017, and 2018–2020, respectively. Treatment time based on treatment modality is shown in Figure S1.

Patients in the delayed treatment group had a greater burden of stage 3 (13.7% vs. 10.8%, P<0.001) and stage 4 (44.8% vs. 41%, P<0.001) disease than the early treatment group (Table 1). Overall, around 44% of patients were diagnosed with stage 4 disease. Patients in the delayed group had larger tumors (48.69 vs. 46.71 mm, P<0.001) of poorer differentiation (40.4% vs. 37.1% poorly differentiated, P<0.001). In terms of treatments, patients who received delayed therapy were more likely to receive chemotherapy (90.3% vs. 79.6%, P<0.001) and radiation (22.4% vs. 20.9%, P<0.001), and less likely to receive surgery (74.8% vs. 56.7% receiving no surgery, P<0.001). Rates of pancreaticoduodenectomy (Whipple’s) (30% vs. 18.1%, P<0.001), total pancreatectomy (4.7% vs. 2.7%, P<0.001), and partial pancreatectomy (7.2% vs. 3.6%, P<0.001) were higher in the early treatment group compared to the delayed treatment group.

Demographic and treatment selection separated by clinical stage are presented in Table 2. Across all stages, patients in the delayed treatment group were less likely to receive surgery. Specifically, early treatment was associated with a higher rate of Whipple surgery for all stages (stage 1, 43.6% vs. 23.5%, P<0.001; stage 2, 59.4% vs. 45.3%, P<0.001; stage 3, 29.4% vs. 18.6%, P<0.001; stage 4, 3.7% vs. 1.8%, P<0.001), though rates of surgery decreased as stage increased, with only 4% of stage 4 patients receiving some form of surgical intervention. Patients with early stage disease (stages 1 and 2) were more likely to receive treatment sooner (30.9% within 1 month) than patients with stages 3 and 4 disease (25.8% within 1 month). For early stage disease, patients who received early treatment received less radiation (stage 1: 19.7% vs. 32.4%; stage 2: 30.5% vs. 33.4%) and chemotherapy (stage 1: 64.4% vs. 81.3%; stage 2: 74.1% vs. 83.8%). Absolute differences in rates of chemotherapy (stage 1 difference: 16.9%, stage 2: 9.7%, stage 3: 6.9%) between TTT groups decreased as stage increased.

Additional analyses were performed based on the time from diagnosis to treatment at 2 months and 3 months (Table S1). Of note, most patients (78%) received initial treatment within 2 months, and nearly all patients (94%) received treatment within 3 months. Patients in both delayed treatment groups (≥2 and ≥3 months) were less likely to receive surgery as their initial therapy than patients in the early (<2 and <3 months, respectively) treatment groups.

Survival analysis

A total of 63,361 patients had complete follow-up and treatment data with an average overall survival time of 14.8 months and were included in survival analyses. Table 3 displays total survival in months, OM, CSM, and NCM based on early or delayed time from diagnosis to treatment. Patients with delayed treatment had 2.5 months less survival time (14.08 vs. 16.69 months, P<0.001) than patients with early treatment. Status at follow-up was no different between groups, though patients with early treatment had higher 6-month OM (34.9% vs. 30.9%) and lower 24-month OM (69.4% vs. 71.6%) than patients with delayed treatment (Table 3). CSM and NCM were not different between time groups at 12 months or at the end of follow-up. Analyses based on 2-month and 3-month TTT thresholds are presented in Table S2. Patients who underwent treatment after 2 months had less total survival time than those who received treatment within 2 months (14.32 vs. 14.96 months, P<0.001). Patients who received treatment within 3 months did not survive longer than patients with treatment after 3 months (14.79 vs. 15.33 months, P=0.06). Similar trends in 6-month, 24-month, and OM were seen in the 2- and 3-month analyses as was seen in the 1-month analysis (Table S2).

Survival outcomes for stages 1–3 and stage 4 tumors by treatment time are presented in Table 4 and Table 5, respectively. Patients with stages 1–3 tumors with delayed treatment had poorer survival than those with early treatment (18.73 vs. 23.72 months, P<0.001), greater OM (74.7% vs. 72.3%, P<0.001), and similar non-cancer mortality. Patients receiving early treatment for stages 1–3 disease were more likely to be alive at follow-up (27.7% vs. 25.3%, P<0.001) and less likely to be dead from cancer (66.5% vs. 69.1%, P<0.001). Patients with stage 4 disease who received treatment after 1 month from diagnosis had greater survival time (9.02 vs. 7.52 months, P<0.001). As seen in Figure 1, patients who received early treatment initially had greater OM than those who received delayed treatment. However, over the duration of the follow-up period, the early treatment group had improved OM than the delayed treatment group (log rank test P<0.001). Kaplan-Meier models for individual clinical stages is seen in Figure S2.

Figure 1 Kaplan-Meier plot for overall survival for stages 1–3 disease based on time to treatment, log rank test P<0.001.

On multivariable Cox proportional hazard modeling for OM for stages 1–3 disease (Table 6), delayed treatment was associated with a crude HR of 1.22 [95% confidence interval (CI): 1.19–1.26, P<0.001] and an adjusted HR of 1.07 (95% CI: 0.96–1.18, P=0.16) using a reference of early TTT. Other variables associated in the multivariate model with increased OM included male sex, black race, household income <$55,000, not receiving surgery, not receiving chemoradiation, poorer histologic differentiation, increased tumor size, and increased clinical stage at diagnosis.

Discussion

In this large, retrospective observational study, we identify several associations between clinical stage, time from diagnosis to treatment, and survival outcomes for patients with PDAC. When including disease of all clinical stages, a time from diagnosis to treatment of less than 1 month was associated with a nearly 50% higher rate of surgery and 2.5 additional months of survival than for patients with treatment initiation after 1 month. These survival and treatment patterns were also seen in a sub-analysis restricted to only potentially resectable disease (stages 1–3). For stage 4 disease, delayed treatment was associated with improved, albeit still exceedingly poor, overall survival. Etiologies for this paradoxical finding are discussed later. Survival benefit was also seen for patients who received treatment within 2 months compared to patients who started treatment after 2 months; there was no survival benefit when comparing patients who received treatment within 3 months compared to after 3 months. The underlying factors explaining these associations are likely multifactorial, with contributions from patients, providers, and the health care systems in which treatment is provided.

Patients with non-metastatic disease (stages 1–3) stand to benefit most from expedited diagnosis and treatment, as surgical resection offers the greatest survival benefit to PDAC, but must be performed before the disease has metastasized and becomes unresectable (18). The increased rates of surgical treatment in patients who undergo early treatment may reflect this desire to operate early on disease that is resectable to minimize the chance for metastatic progression. Social determinants of health (SDOH) such as inconsistent transportation, language barriers, poor health literacy, and rurality of home address have been implicated in delays and outcome disparities in other malignancies, and may play a role in delays associated with PDAC therapy (16,19,20). Interestingly, the improvement in OM in the early treatment cohort was not seen in the first 6 months, during which time the early treatment group had higher OM. Taking into consideration the higher rates of surgery (44% vs. 25.7%) in the early treatment group, this initial decrease in survival could reflect post-surgical complications and is supported by the fact that at 1 year and onwards, survival favors the early treatment group, which would then consist of patients who have recovered from their index surgeries. Another possible explanation for treatment delays ≥1 month in our study is the higher burdens of advanced stage and poorer grade disease in this cohort. Hopstaken et al. reported that complex cases which require workup at multiple centers are associated with diagnostic and treatment delays in PDAC (21). Interestingly, the proportion of patients receiving treatment within 1 month of diagnosis decreased over the course of the study period, which may reflect the time needed for multi-disciplinary approach to care that has been recommended in pancreatic cancer guidelines (22). We note that this observation and our findings may be contradictory to the recent reports of improvements in the five-year survival rate for PDAC observed in the last three years, however, it is possible that an even greater survival benefit may be been seen if these multi-disciplinary regimens were started with minimal delay. Additionally, TTT for newer chemotherapy regimens may be affected by technical considerations. For example, modified FOLFIRINOX requires port placement which may require additional coordination and can induce potential confounding treatment delays versus other regiments that can be administered peripherally such as gemcitabine and abraxane. Ultimately, given the improved survival and increased rates of surgery associated with shorter times to treatment, efforts should be made by providers and healthcare systems to streamline decision making after diagnosis of PDAC, especially for those patients with resectable and borderline resectable disease at diagnosis.

Perhaps counter-intuitively, delayed treatment in stage 4 disease was not associated with poorer overall survival. However, this finding has been previously reported and etiologic causes are multifactorial (22,23). Contributing factors include the inherently aggressive nature of some PDAC for which chemoradiation therapies may be ineffective. Also possible is that patients receiving delayed treatment were less symptomatic, and therefore clinically there was less urgency to start chemotherapy quickly. Reciprocally, this may reflect a bias towards more aggressive disease in the early treatment group which may account for the poorer survival. Along the same vein, the effect of each patient’s unique presenting symptom on TTT should be considered. Certain symptoms such as malignant bowel obstruction or jaundice need to be managed before treatment can be started, resulting in delays. For example, obstructive jaundice delays treatment initiation as conventionally, total bilirubin <2 mg/dL and aspartate aminotransferase (AST)/alanine aminotransferase (ALT) <3× upper limit of normal are preferred before chemotherapy initiation. In contrast, other presenting symptoms such as pain or weight loss do not result in treatment delays. This possibility was also suggested by Gobbi et al., and it could play a role in the present analysis (8). Finally, patient comorbidity could be affecting treatment decisions. For instance, patients who ultimately elected for hospice care within 1 month may have had a greater burden of comorbidity than candidates who received delayed systemic chemotherapy, and therefore explains the non-inferior survival of patients in the delayed therapy group due to them being able to receive palliative therapy, which then prolongs survival (24). Future studies that incorporate clinical data such as CA19-9 and follow patients prospectively are needed to elucidate these likely complex associations further, especially considering the recent concerning observations of increased incidence rate of PDAC in younger female patients of non-white ethnicity (25,26).

Strengths of our study include its large sample size over a decade-long study period inclusive of regions from the entire United States. Sub-analyses based on clinical stage help to isolate resectable versus unresectable disease. There are limitations in our analysis that warrant discussion. First, the retrospective nature may lead to confounding however, with the aforementioned sample size and multivariable proportional hazards regression models, we believe the effect of any unexpected confounders to be minimal or at least equally dispersed between groups. As with all retrospective database studies, misclassification/misattribution bias and selection bias may affect our results. However, SEER represents the largest, most authoritative cancer registry in North America with excellent validation in real-world cohorts. As with all observational studies, immortal time bias should be mentioned, but the Kaplan-Meier modeling demonstrates diverging survival curves beyond the initial months from diagnosis, which reassures against patients who died before treatment initiation significantly affecting our results. Second, SEER does not provide treatment intent (i.e., palliative or curative) or comorbidity data which is a critical factor in cancer-related research as performance status is a primary driver for chemotherapy and surgical decisions; future prospective studies are needed examining associations between comorbidities, TTT, and outcomes in curative intent patients. Third, the relationship between the timing of surgery and chemoradiation is not provided. Therefore, we were unable to determine if chemotherapy was completed in a neoadjuvant or adjuvant fashion. As it pertains to PDAC, this is relevant because of patients with borderline resectable disease at diagnosis. In this group, upwards of 50% who receive neo-adjuvant chemotherapy will allow for tumor downsizing and subsequent curative intent surgical resection. The total doses of chemoradiation are also not currently provided in this iteration of SEER and cannot be quantified. Because we cannot identify borderline resectable patients due to inherent limitations in the data provided, this cohort should remain an important area for future investigations. Finally, though the absolute differences in survival rates were rather small (1–3%), we believe that when scaled to a US population with a rising incidence, small differences in mortality can rapidly become magnified, especially when they are based on patient-related socioeconomic disparities rather than tumor characteristics.

Conclusions

In conclusion, treatment within 1 month of diagnosis was associated with disparities in survival in patients with pancreatic adenocarcinoma. On subgroup analysis, patients with earlier stage (stages 1–3) disease showed the greatest survival improvement and therefore stand to benefit most from expedited treatment. Our study adds to the expanding literature elucidating associations between SDOH, timing of treatment, and patient outcomes. Given the nature of late presentation of PDAC, the role of the skilled gastroenterologist within the multidisciplinary team is crucial to earlier diagnoses and expediting treatment.

Acknowledgments

Funding: None.

Footnote

Peer Review File: Available at https://apc.amegroups.com/article/view/10.21037/apc-24-10/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://apc.amegroups.com/article/view/10.21037/apc-24-10/coif). V.M.S. is a consultant for Olympus Medical and Cook Medical. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study’s ethical approval was exempt by the institutional ethics board of The University of Virginia and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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