A comparison of outcomes for patients with localized pancreatic ductal adenocarcinoma receiving neoadjuvant chemotherapy with and without radiation prior to curative-intent resection: an analysis of the National Cancer Database

Introduction

In the United States, pancreatic cancer, specifically pancreatic ductal adenocarcinoma (PDAC), has recently become the 3^rd-leading cancer-related cause of death (1). By 2030, it is expected to become the 2^nd in cancer-related death (2). Currently, the gold standard for PDAC treatment is surgical resection with curative intent, but this is problematic as only 20% of PDACs are resectable at time of diagnosis (3). As such, neoadjuvant therapy—such as chemotherapy alone or chemotherapy followed by radiation—has provided an opportunity to enhance patient outcomes for patients with this malignancy with recent work demonstrating improvements in overall survival (OS) (4-6).

According to the National Comprehensive Cancer Network (NCCN) guidelines, neoadjuvant therapy can be used in the setting of resectable to locally advanced PDAC, specifically in patients with poor prognostic features (7,8). Considering the optimal treatment for PDAC, the goal of neoadjuvant treatment is to enhance tumor resectability, and it may also play a role in mitigating the risk of disease relapse following resection (8,9). Further, supplemental radiation has been demonstrated as causing increased rates of nodal downstaging and R0 resection in borderline resectable PDAC tumors, which is associated with improved survival in these patients (10,11). Moreover, Chopra et al. [2021] and Nagakawa et al. [2019] has demonstrated neoadjuvant chemotherapy with radiation (NCR) is associated with lower lymph node positivity and lymphovascular invasion after matching to neoadjuvant chemotherapy, further adding weight to the impact of this modality on improving surgical and patient outcomes (12,13). Although surgical and treatment outcomes improved in the groups receiving neoadjuvant chemotherapy and radiation, neither group demonstrated improved OS for these patients, but Chopra et al. [2021] did note improved disease-free survival for the group receiving both modalities (12,13). As such, evidence is contradictory as to whether radiation should be given following neoadjuvant chemotherapy initiation.

Currently, no specific modality has been decided as the most optimal approach for patients with local PDAC. Specifically, the NCCN guidelines recommend some form of chemotherapy alone or chemotherapy with radiation for neoadjuvant treatment (7). Considering that the addition of radiation to chemotherapy may improve surgical outcomes with contradictory improvement in survival (8,10-15), it becomes necessary to further evaluate how survival is impacted by patients receiving radiation with neoadjuvant chemotherapy when compared to neoadjuvant chemotherapy alone (NC). Additionally, research has demonstrated that we are developing better techniques, such as stereotactic-magnetic resonance-guided adaptive radiation, and understanding of the benefits of neoadjuvant radiation in different PDAC tumors, suggesting increased necessity for more recent research to determine if outcomes are now improving overall (16). Therefore, evaluation of recent data may provide more robust insight into the impact of neoadjuvant radiation after chemotherapy initiation on surgical and prognostic outcomes.

In our study, we aim to identify differences between demographics and tumor characteristics in patients receiving NC or NCR. Further, we compare surgical outcomes, treatment outcomes, and survival rates between the two cohorts using a retrospective cohort analysis of the National Cancer Database (NCDB) from 2015–2020. We present this article in accordance with the STROBE reporting checklist (available at https://cco.amegroups.com/article/view/10.21037/cco-25-60/rc).

Methods

Ethical statement

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Building cohort

Using the NCDB Participant User Files, we selected for all patients diagnosed with PDAC from 2015–2020 using the Histology Code “8140”. Using the American Joint Committee on Cancer (AJCC) staging system, only patients with localized clinical staging (1, 1A, 1B, 2, 2A, 2B, and 3) were included in the final cohorts. It is important to note that different variables were used for clinical staging due to transitioning from the “TNM_CLIN_STAGE_GROUP” variable to “AJCC_TNM_CLIN_STAGE_GRP” in 2018. Any patients who did not receive curative-intent resection were excluded. Additionally, patients were excluded if they did not receive neoadjuvant chemotherapy prior to resection. Patients were also excluded if they did not receive neoadjuvant radiation with chemotherapy, it was unknown when radiation was received, they did not have information on R0 resection status, they received neoadjuvant radiation within 30 days of neoadjuvant chemotherapy initiation, or they received adjuvant radiation as well. We elected to not include patients receiving adjuvant radiation to improve the robustness of our model in assessing for the benefit of neoadjuvant radiation after chemotherapy alone. Further, we also chose to exclude patients receiving neoadjuvant radiation within 30 days of chemotherapy initiation to select for patients not receiving the therapies concurrently.

Patients were then classified into two groups: NC or NCR. The NCR group included only patients receiving a round of radiation at least 30 days after the initiation of chemotherapy. Patients were first classified by whether they received neoadjuvant chemotherapy prior to resection using the “RX_SUMM_CHEMO” variable for either single or multi-agent regimens. From there, patients who did not receive chemotherapy prior to surgery were excluded using the “RX_SUMM_SYSTEMIC_SUR_SEQ” variable. Once this was classified, patients were also stratified by whether they received radiation or not using the “RX_SUMM_SURGRAD_SEQ” variable, excluding patients who also received adjuvant radiation. Further, patients needed to receive radiation 30 days after chemotherapy start day as well.

Demographics and clinical outcomes

Once cohorts were classified, demographic and clinical outcomes were quantified after stratifying by cohort. These variables included: age, sex, race, insurance type, facility type, primary site of tumor in pancreas, tumor size, resection status, cumulative grade, Charleson-Deyo comorbidity score, clinical staging (AJCC), pathologic staging (AJCC), 30-day mortality, 90-day mortality, vital status, node status, staging change, and year of diagnosis. Depending on variable type, univariate models assessed the heterogeneity between the cohorts using the Chi-squared test of independence for categorical Variables and the one-way t-test for continuous variables. Heterogeneity and significant findings were assumed when P<0.05. Further, we also classified patients in each cohort comparing clinical AJCC T stage, pathologic AJCC T stage, and lymphovascular invasion status. For patients receiving radiotherapy, we quantified the different modalities, external beam planning technique, and total dose.

Multivariate generalized logistic regressions were utilized to determine if there were different odds of outcomes between the NC and the NCR cohorts. Covariates for these models were age, sex, race, insurance status, primary site, clinical staging, tumor size, and Charleson-Deyo comorbidity score. The logistic regressions assessed for the odds of event for the NC group when compared to the NCR cohort for these variables: R0 resection, 30-day mortality, 90-day mortality, vital status, positive regional lymph node status, downstaging status following neoadjuvant treatment, and upstaging status following neoadjuvant treatment. Odds ratios (ORs) that are greater than 1 are assumed to have higher odds of event. These findings were then compiled into a forest plot for visualization of outcomes. Finally, univariate t-test analyzed if there were differences in clinical staging after changing all staging levels to “1” if originally “1A” and “1B” or “2” if originally “2A” or “2B”. Every other stage remained the same.

Neoadjuvant therapy trends

From 2015–2020, we quantified the utilization of NC and NCR for patients with localized PDAC on clinical staging. Univariate linear regressions were conducted to determine if utilization of NC and NCR changed by year. An interactive model using year of diagnosis and cohort assessed for differences in the rate of change by year. Further, we also analyzed the time to radiation initiation following chemotherapy initiation in the NCR cohort using univariate linear regression as well. We also performed a subgroup analysis for these patients who also received adjuvant chemotherapy. Graphs were created to visualize the changes by year.

Survival analysis

Prior to survival analysis, cohorts were 1:1 propensity-score-matched between the NC and NCR cohorts using the variables: age, sex, race, insurance status, primary site, clinical staging, tumor size, and Charleson-Deyo score. With the matched cohorts, Cox proportional hazards models were utilized to assess for time-based survival differences via hazard ratio (HR). The outcomes analyzed were OS and 1-year survival. For OS, survival dates were determined using the date of last contact from initial diagnosis. For 1-year survival, dates were censored at date of death if patients died before the full timeframe or 12 months (1 year) if still alive. Following the Cox proportional hazards models, Kaplan-Meier curves were built to visualize the effect on survival. Cox proportional hazards models were compiled into forest plots to visualize the impact on survival. For 1-year survival, generalized logistic regressions also quantified ORs based on cohort after propensity-score matching. Any patients with missing data that were necessary for analyses were removed, and the last date of follow-up for survival analyses was the last date of communication with patient or their death.

Results

Inclusion and exclusion

First, we wanted to select for patients with localized PDAC who received neoadjuvant chemotherapy or neoadjuvant chemotherapy initiation 30 days prior to radiation before they received curative-intent resection. Originally, there were 160,037 patients with PDAC diagnosis from 2015–2020. After filtering for all other criteria, there were 6,472 patients who received either neoadjuvant chemotherapy with or without radiation prior to resection (Figure 1).

Figure 1 Patient selection using inclusion and exclusion criteria. PUF, Participant User Files.

Demographics and outcomes

We compared the demographics and tumor characteristics of the NCR and NC cohort. Overall, there were 2,117 (32.7%) patients in the NCR cohort and 4,355 (67.3%) in the NC cohort (Table 1). On univariate analysis, the NCR cohort is associated with younger age [NC: 65.8 years, standard deviation (SD) =9.3 years; NCR: 64.6 years, SD =9.2 years; P<0.001], different insurance status (P=0.002), different facility types (P<0.001), different Charleson-Deyo comorbidity scores (P=0.001), and different distributions by year (P<0.001). Additionally, the rate of adjuvant chemotherapy utilization is lower in the NCR cohort (23.3% vs. 35.6%, P<0.001). There were no differences in cohorts when assessing sex (P=0.08) and race (P=0.51). The average time to follow-up from initial diagnosis was 852.7 days.

We then compared tumor characteristics and outcomes for patients. Univariate analysis reveals a difference in primary tumor site distribution (P<0.001), differences in clinical staging (P<0.001), differences in pathologic staging (P<0.001), lower positive node status in the NCR cohort (NCR: 31.9%; NC: 52.3%; P<0.001), and differences in stage changing following neoadjuvant treatment (P<0.001). Table 1 depicts these values for each variable.

We also assessed differences in staging and lymphovascular invasion for the two cohorts. In terms of clinical staging, the NCR cohort had a higher mean clinical stage of 1.85 compared to NC with 1.59 (t=13.72, df=3,761.5, P<0.001). Despite higher clinical staging, the NCR cohort was associated with a lower mean pathologic staging (1.72 vs. 1.87, t=5.1, df=1,500, P<0.001). For clinical and pathologic T staging, we note differences in distribution between each cohort (P<0.001 for both). For lymphovascular invasion, we note more lymphovascular invasion (41.6% vs. 21.2%, P<0.001) in the NC cohort as well.

Table 2 provides information on radiation for the NCR cohort. In terms of radiation modality, 1,592 (75.2%) received photons. Stereotactic body radiation therapy (SBRT) accounted for 388 (18.3%) patients, while intensity-modulated radiation therapy (IMRT) accounted for 937 (44.3%) of the patients; 1,200 patients (61.3%) received a total dose between 4,500–5,500 cGy.

Utilization trends

Given the increase in interest in radiation in neoadjuvant therapy, we sought to assess the utilization of neoadjuvant chemotherapy prior to neoadjuvant radiation. On univariate linear regression, the NC cohort was associated with an increase of +166.7 cases per year (P<0.001). However, the NCR cohort had a positive increase in cases by year with +35.1 cases per year, but this correlation was not statistically significant (P=0.07, Figure 2A). Univariate comparison of the trends indicated that the NCR cohort had a smaller increase each year, with the NC cohort increasing by +131.6 more cases per year (P<0.001).

Figure 2 Therapy trends and characteristics from 2015–2020. (A) Total number of cases by year for neoadjuvant chemotherapy prior to radiation (gray) and neoadjuvant chemotherapy only (black) in the setting of localized PDAC. (B) Average days to radiation initiation after chemotherapy initiation for the NCR cohort by year. The P value indicates a positive correlation between year of diagnosis and time to radiation initiation. (C) Trends of neoadjuvant and adjuvant utilization in patients with local PDAC. NC, neoadjuvant chemotherapy alone; NCR, neoadjuvant chemotherapy with radiation; PDAC, pancreatic ductal adenocarcinoma; w/, with; w/o, without.

In terms of radiation timing after chemotherapy initiation, we noticed an increased time each year, with an average change of 5.6 days/year (P<0.001, Figure 2B).

We also performed a subgroup analysis of the NC and NCR cohorts based on whether they received adjuvant chemotherapy (Figure 2C). For adjuvant chemotherapy, univariate linear regression reveals an increase of 60.9 cases per year for the NC cohort (P<0.001) but a non-significant increase of 6.4 cases per year in the NCR cohort (P=0.25). In terms of patients not receiving adjuvant chemotherapy, the NC cohort had an increase of 105.8 cases per year (P<0.001), while the NCR cohort had an increase of 28.6 cases per year (P=0.045).

When assessing rate-of-change differences for the NCR cohort, univariate analysis reveals that the NCR cohort without adjuvant chemotherapy does not have a larger increase than these patients receiving adjuvant chemotherapy (+22.2 cases per year, P=0.08), but this value is approaching statistical significance. For the NC cohort, we note a significant difference in the trends over time between those who utilized adjuvant or no adjuvant chemotherapy, with the latter having an increased rate of +44.9 cases per year (P=0.007).

Treatment and surgical outcomes

After assessing trends, we also wanted to compare patient outcomes between the NCR and NC cohorts when controlling covariates. Compared to the NC cohort for postoperative outcomes, the NCR cohort is associated with lower OR for pathologic node status [OR =0.42, 95% confidence interval (CI): 0.38–0.48, P<0.001], higher odds of downstaging tumor (OR =2.15, 95% CI: 1.71–2.71, P<0.001), lower odds for upstaging tumors (OR =0.45, 95% CI: 0.36–0.585, P<0.001, and lower odds of receiving adjuvant chemotherapy (OR =0.56, 95% CI: 0.49–0.64, P<0.001). All other variables did not show a significant difference in odds (Figure 3).

Figure 3 Forest plot depicting outcomes following PDAC resection for the neoadjuvant chemotherapy prior to radiation cohort compared to the neoadjuvant chemotherapy cohort. CI, confidence interval; PDAC, pancreatic ductal adenocarcinoma.

Survival analysis

We sought to understand how the NC and NCR cohorts affect survival in these patients. After 1:1 propensity-score matching, the NCR cohort had better OS with an HR of 0.88 (95% CI: 0.80–0.97, P=0.01). Additionally, the NCR had a better 5-year survival (HR =0.88, 95% CI: 0.80–0.97, P=0.009) and 1-year survival (HR =0.50, 95% CI: 0.40–0.64, P<0.001) after controlling for covariates (Figure 4).

Figure 4 1:1 propensity-matched Cox proportional hazards outputs for the neoadjuvant chemotherapy cohort for overall survival and 1-year survival. The neoadjuvant chemotherapy prior to radiation cohort is associated with better survival across both metrics. CI, confidence interval; PDAC, pancreatic ductal adenocarcinoma.

We next compared survival between the patients who received neoadjuvant chemotherapy and neoadjuvant chemotherapy prior to radiation. Figure 5A portrays the Kaplan-Meier curve for OS between the two cohorts. The NC cohort has a median OS of 32.7 months (95% CI: 30.4–36.1) and the NCR cohort has a median OS of 34.6 months (95% CI: 32.8–37.0). The NCR cohort has better OS than the NC cohort after 1:1 propensity-matching (HR =0.88, 95% CI: 0.80–0.97, P=0.01).

Figure 5 Kaplan-Meier curves depicting survival based on cohort. (A) Kaplan-Meier curve of overall survival for neoadjuvant chemotherapy only (black) and neoadjuvant chemotherapy prior to radiation (gray) in the setting of localized PDAC following curative-intent resection. (B) 1-year survival for the neoadjuvant chemotherapy cohort (black) and the neoadjuvant chemotherapy prior to radiation cohort (gray) in the setting of localized PDAC following curative-intent resection. The y-axis is scaled from 0.85–1.00 to better visualize the difference. PDAC, pancreatic ductal adenocarcinoma.

For 1-year survival, the NC cohort has a lower survival rate of 87.2% (95% CI: 83.2–87.3%) than the NCR cohort rate of 93.2% (95% CI: 90.1–93.3%). After propensity-score matching, the NCR cohort has a lower time-based risk of 0.50 (95% CI: 0.40–0.64) when compared to the NC cohort (Figure 5B). On propensity-matched logistic regression, the NCR cohort had lower odds of passing at 1-year (OR =0.497, 95% CI: 0.387–0.638, P<0.001).

Discussion

Overall, our study aims to provide insight into differences in cohort characteristics, treatment outcomes, and survival for patients who receive neoadjuvant chemotherapy or NCR in the setting of localized PDAC. Moreover, we also assess trends in utilization and treatment characteristics of these cohorts. In doing so, we hope to provide researchers, clinicians, and patients with practical insight into the best neoadjuvant therapy modalities and demonstrate the direction in which current practices are moving.

The cohorts demonstrate differences across several different variables. First, the NCR cohort is associated with younger age, a different distribution of Charleson-Deyo comorbidity score, differences in insurance status, and differences in facility type where they received treatment. In terms of tumor characteristics, the NCR cohort has higher clinical staging, lower pathologic staging, lower pathologic node status, and a greater rate of downstaging. After controlling for covariates, we find that patients in the NCR cohort have lower odds of pathologic node status, higher odds of downstaging, lower odds of upstaging when compared to the NC cohort, and lower odds of receiving adjuvant chemotherapy. However, there are no differences in R0 resection, 30-day mortality, and 90-day mortality between groups. Moreover, propensity-matched models reveal that the NCR cohort has higher odds and improved time-based risk for OS, 1-year survival, and 5-year survival. Finally, an analysis of trends reveals that utilization of NCR is increasing at a slower rate than the increase in the rate of NC each year, and radiation initiation after beginning chemotherapy is starting later each year on average. Additionally, the NC cohort without adjuvant chemotherapy shows a greater rate of increase over time compared to the NC cohort that received adjuvant chemotherapy. In contrast, no such difference in temporal trends is observed between the adjuvant and non-adjuvant groups within the NCR cohort.

In terms of demographic variables, our results reveal differences in age, insurance status, and facility type between the two cohorts. Specifically, NCR is more frequently given to patients at lower age and lower Charleson-Deyo comorbidity scores. This follows along the same lines of Hays et al. [2025] who found that older patients are less likely to receive multimodal treatment for PDAC, which may be due to concerns with the inability to tolerate multimodal treatment as patients age (17). Further, their work would also explain why comorbidity counts are greater in the older NC cohort in our study (17). Beyond these factors, NCR patients also have a higher proportion receiving treatment at academic programs and are on private or managed care insurance plans, whereas the NC cohort has more patients on Medicare and receiving treatment at Comprehensive Community or Integrated Network Cancer Programs. Although more research is needed into why this occurs, the differences in where patients receive neoadjuvant chemotherapy prior to radiation may be due to greater availability of radiation technologies at these academic programs. Further, the differences in patients on Medicare or on private plans may also be due to the age differences we show between the two cohorts.

To our knowledge, this is the first study to evaluate utilization trends for patients receiving neoadjuvant chemotherapy or neoadjuvant chemotherapy prior to radiation using the NCDB. Considering that our study found increased utilization of neoadjuvant chemotherapy each year, this may suggest that clinical guidelines have become more likely to endorse neoadjuvant chemotherapy due to its benefit in improving survival and surgical outcomes (7,18). However, this finding was not replicated with the neoadjuvant chemotherapy prior to radiation group, which corroborates the conflicting evidence of radiation in improving outcomes for patients (9,12,13,15,16,19-23). When looking at time to radiation initiation following chemotherapy initiation, we noted an increase in time from 2015–2020, with initiation ranging from around 110 to 140 days. This result could suggest that more patients who receive radiation after chemotherapy are utilizing total neoadjuvant treatment (TNT) method, which is usually characterized by 3–4 months of chemotherapy followed by 5–6 weeks of radiation (24). Interestingly, this finding contradicts recent work by Su et al. [2025] that found decreasing utilization of perioperative chemoradiotherapy in the US Surveillance, Epidemiology, and End Results (SEER) dataset in our timespan (25). It is important to note that we only looked at neoadjuvant therapy alone as compared to their perioperative perspective, so our results may suggest greater utilization of the treatment preoperatively to increase the opportunity for successful resection and lower disease burden prior to the operation. Further, we did not include adjuvant radiation as well due to limited information on the topic and to improve the robustness of our model. Lastly, increased utilization of neoadjuvant therapy in general significantly improves the rate of R0 resection and disease-free survival in borderline-resectable cases as compared to up-front surgery, so there may be less necessity for post-operative radiation in general (4,25,26).

Multiple studies have established a role of neoadjuvant therapy in improving outcomes for patients with non-metastatic PDAC compared to up-front surgery (13,19,21,27-30). The current understanding is that neoadjuvant therapy, specifically FOLFIRINOX or gemcitabine with nab-paclitaxel, may play a role in improving survival and increasing the odds of R0 resection in patients with resectable or borderline resectable PDAC (13,28,29). However, the role of radiation in the setting of local PDAC is not-well characterized with studies finding conflicting results about its benefit to patients (5,11,13,19,21,27,28,31,32). Oba et al. [2022] performed a retrospective analysis of the NCDB from 2010–2016, noting an increased rate of R0 resection in the NCR cohort, a higher rate of 90-day mortality, and no difference in OS between groups (19). The survival findings were also replicated in Hammel et al. [2016] and Nagakawa et al. [2019] (13,21). Compared to Oba et al. [2022] (19), there are some differences with our study. First, we utilized a propensity-matched model to better identify homogeneous patients for a more robust comparison of survival outcomes with these cohorts. Secondly, our results are more recent, which may provide greater weight to our outcomes as our understanding of neoadjuvant radiation in PDAC has improved in recent years (16). When comparing our results, we found that the rate of R0 resection and 90-day mortality did not differ between these two groups, but we did identify improved OS in NCR patients. Despite worse clinical staging in the NCR cohort, we also noted greater odds of tumor downstaging, lower odds of pathologic node positivity, lower odds of tumor upstaging, and decreased utilization of adjuvant chemotherapy when compared to the NC cohort. Patients in the NCR cohort also had improved 1- and 5-year survival, as well as lower odds of passing at the 1-year mark. The 1-year survival improvement could possibly be explained by the decreased likelihood of receiving adjuvant chemotherapy in the NCR cohort, as these patients may have improved systemic control and lower occurrences of micrometastases and lymphovascular invasion leading to improved short-term survival (22,33). Therefore, our study provides support for the use of neoadjuvant radiation after chemotherapy induction as it may improve surgical outcomes and mitigate short-term complications following curative-intent resection.

To our knowledge, our study is the largest retrospective study to demonstrate improved OS for patients receiving radiotherapy after chemotherapy when compared to chemotherapy alone. This finding could be explained by greater understanding of the proper application of radiotherapy and better technical capabilities of these machines (26). Moreover, this may justify the trend of increased time between chemotherapy and radiation initiation that we see in our work as it may suggest that physicians are using chemotherapy for longer in these patients to achieve systemic control, which is an important factor in the success of radiation treatment (26).

Currently, the literature argues that R0 resection, tumor staging, tumor size, and pathologic node status are some of the most important prognostic variables in PDAC (34). In our study, we find higher clinical staging in the NCR cohort, but a greater likelihood of downstaging the tumor and negative node status when compared to the NC cohort on multivariate analysis. Altimari et al. [2023] and Miccio et al. [2021] found increased rates of negative pathologic node status and greater likelihood in nodal downstaging for the NCR cohort as well, but their results differ from ours as they do not see improved survival in the NCR cohort despite these changes (11,20). It is important to recognize that we focused directly on overall staging, while the other works focused on nodal downstaging. Recent work by Chawla et al. [2020] has revealed that clinical staging may not correctly demonstrate the extent and burden of the disease in PDAC, which may explain the discrepancy between survival and improved node staging in Altimari et al. [2023], Miccio et al. [2021], and our own work (11,20,35). However, the PREOPANC trial demonstrated improved survival in patients receiving neoadjuvant chemotherapy and radiation with negative node status and R0 resection, but this was compared with patients who only received up-front surgery (30). In terms of R0 resection, we note no difference in margin-negative resection between the NCR and NC cohort, despite it being associated with better outcomes in patients (34). Further, in patients who received resection, the PREOPANC-2 trial showed no difference in OS and margin-negative resection between patients receiving neoadjuvant FOLFIRINOX and gemcitabine-based chemotherapy with radiation (36). This further adds to the need to determine the importance of surgical metrics in improving outcomes. In either case, our work utilizes a robust approach via propensity-score matching to draw meaningful conclusions on the impact of radiation on survival, but more work needs to be completed to identify the best prognostic factors for local PDAC treatment (37). Specifically, the relationship between staging, node status, R0 resection, and survival is crucial to define if we want to improve our understanding of prognosis in PDAC patients.

It is important to address some limitations in our study. First, our study is a retrospective analysis, which is subject to larger levels of bias and data missingness. Second, although we did consider several prognostic features, we did not evaluate some important factors for PDAC, such as carbohydrate antigen 19-9 (CA 19-9) levels, genetic mutations, and vascular invasion, due to limitations of the dataset. We also were unable to account for specific treatment regimens and agents due to limitations in the dataset. Likewise, our study could not assess for relapse rates in these patients and did not consider the complications that can come with radiation that are important for clinical decision-making. Finally, we were unable to determine if patients who were unable to receive adjuvant chemotherapy despite having indications for it following curative-intent resection.

Conclusions

This study demonstrates that NCR is associated with negative node status, improved tumor downstaging, and better short-term and long-term survival outcomes in patients with localized PDAC. Although there is no difference in R0 resection and perioperative mortality between cohorts, the survival benefit in the NCR cohort highlights the potential value of incorporating radiation with neoadjuvant chemotherapy. As utilization of neoadjuvant therapy continues to develop, our results can help to inform treatment planning and provide direction for future research in perioperative management of PDAC.

Acknowledgments

We gratefully acknowledge Becky Gohmann and family for their generous philanthropic support, which made this work possible.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://cco.amegroups.com/article/view/10.21037/cco-25-60/rc

Peer Review File: Available at https://cco.amegroups.com/article/view/10.21037/cco-25-60/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://cco.amegroups.com/article/view/10.21037/cco-25-60/coif). A.C. serves as an unpaid editorial board member of Chinese Clinical Oncology from April 2024 to March 2026. 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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

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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