Impact of preoperative body weight on short-term and long-term prognosis after pancreatic resection for pancreatic ductal adenocarcinoma: a multicenter study
Original Article

Impact of preoperative body weight on short-term and long-term prognosis after pancreatic resection for pancreatic ductal adenocarcinoma: a multicenter study

Judong Li1#, Ting Niu1#, Ligang Shi1#, Xiaowei Deng1#, Xunan Mao1,2#, Guang Yang1, Xing Liang1, Meng Ji1, Liang Tang1, Danlei Chen1, Anan Liu1, Xinliang Lv3, Lijun Hu4, Xiaoyong Wang5, Wei Wu6, Chenghao Shao1

1Department of Pancreatic-biliary Surgery, Shanghai Changzheng Hospital, Naval Medical University, Shanghai, China; 2Department of Medical College, Yangzhou University, Yangzhou, China; 3Department of Hepatobiliary and Pancreatic Surgery, Lishui Municipal Central Hospital, Lishui, China; 4Department of General Surgery, Changshu First People Hospital, Changshu, China; 5Department of Gastrointestinal Surgery, People’s Hospital of Haimen City, Haimen, China; 6Department of General Surgery, Lu’an People’s Hospital of Anhui Province, Lu’an, China

Contributions: (I) Conception and design: C Shao, J Li, C Shao, W Wu, X Wang, L Hu, X Lv, J Li, T Niu, L Shi, X Deng, X Mao; (II) Administrative support: L Tang, D Chen, A Liu, C Shao; (III) Provision of study materials or patients: J Li, T Niu, L Shi, X Deng, X Mao; (IV) Collection and assembly of data: All authors; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Prof. Chenghao Shao, MD. Department of Pancreatic-biliary Surgery, Shanghai Changzheng Hospital, Naval Medical University, No. 415 Fengyang Road, Shanghai 200003, China. Email: shaochenghao@smmu.edu.cn; Prof. Wei Wu, MD. Department of General Surgery, Lu’an People’s Hospital of Anhui Province, Lu’an, China. Email: wu13956128634@sina.com; Prof. Xiaoyong Wang, MD. Department of Gastrointestinal Surgery, People’s Hospital of Haimen City, Haimen, China. Email: fy4778@163.com.

Background: The prognostic implications of preoperative body mass index (BMI) in patients undergoing curative-intent pancreatic resection for pancreatic ductal adenocarcinoma (PDAC) remain poorly characterized, with existing evidence demonstrating contradictory findings. This multicenter cohort study comprehensively analyzes the association between BMI stratification and both perioperative outcomes and long-term survival in PDAC patients receiving surgical intervention.

Methods: Study participants were stratified into three predefined BMI strata: low-BMI group (BMI <18.5 kg/m2), normal-BMI group (BMI 18.5–25.0 kg/m2), and high-BMI group (BMI >25.0 kg/m2). Demographic parameters, operative profiles, and postoperative outcomes of the patients were compared. Univariable and multivariable analyses were performed to investigate the risk factors for short-term and long-term outcomes after pancreatic resection for PDAC.

Results: Multivariable analyses revealed that both low-BMI and high-BMI were associated with significantly elevated mortality [odds ratio (OR) 4.952, 95% confidence interval (CI): 1.238–19.799, P=0.02, and OR 3.911, 95% CI: 1.134–13.491, P=0.03] and overall morbidity (OR 2.008, 95% CI: 1.149–3.509, P=0.01, and OR 1.820, 95% CI: 1.191–2.783, P=0.006). In addition, multivariable Cox-regression analyses revealed that both preoperative low-BMI and high-BMI were independent predictors of OS [hazard ratio (HR) 1.410, 95% CI: 1.049–1.896, P=0.02 and HR 1.609, 95% CI: 1.274–2.034, P<0.001] and RFS (HR 1.395, 95% CI: 1.050–1.853, P=0.02 and HR 1.575, 95% CI: 1.249–1.987, P<0.001).

Conclusions: Patients with low-BMI and high-BMI demonstrate a significantly worse prognosis compared to those with normal-BMI following pancreatic resection for PDAC.

Keywords: Pancreatic ductal adenocarcinoma (PDAC); body mass index (BMI); postoperative morbidity; overall survival (OS); recurrence-free survival (RFS)


Submitted Dec 09, 2025. Accepted for publication Feb 25, 2026. Published online Mar 27, 2026.

doi: 10.21037/jgo-2025-1-1022


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Introduction

Pancreatic ductal adenocarcinoma (PDAC), the predominant form of pancreatic malignancy, constitutes over 90% of exocrine pancreatic cancers. Characterized by aggressive biological behavior, PDAC demonstrates a dismal 5-year survival rate primarily attributed to its propensity for locoregional invasion, distant metastasis, high recurrence frequency, and surgical inoperability in most cases (1-3). Postoperative complications following resection not only correlate with extended hospital stays and increased healthcare expenditures but also influence disease recurrence patterns and overall survival (OS) outcomes (4,5). The identification of modifiable risk factors associated with both surgical complications and long-term oncological results remain essential for optimizing therapeutic strategies and improving prognostic trajectories in resectable PDAC.

Multiple perioperative variables have been identified as determinants of postoperative outcomes following PDAC resection, including but not limited to patient demographics (age, sex), clinical parameters [American Society of Anesthesiologists (ASA) score, comorbidities], tumor characteristics (ductal dimensions, tumor size, vascular invasion), biochemical markers [carbohydrate antigen 19-9 (CA19-9)], and operative factors (procedure duration, intraoperative blood loss, transfusion requirements) (6-8). Growing evidence from contemporary research underscores the prognostic significance of nutritional status in pancreatic resection outcomes, with emerging data revealing its critical association with postoperative recovery and oncological prognosis (9-11). Notably, the prognostic relevance of preoperative body mass index (BMI), a readily accessible surrogate marker of nutritional status, remains controversial in PDAC surgical management, with conflicting evidence regarding its predictive value (12-15). Furthermore, current literature exhibits a predominant focus on obesity-related outcomes, while the clinical implications of low BMI, a prevalent condition among pancreatic cancer patients, have been insufficiently addressed in existing prognostic models (13-16). This knowledge gap is particularly evident in the context of PDAC-specific investigations, where the association between subnormal BMI and postoperative complications coupled with long-term survival remains underexplored.

To address these limitations, our study employs a tripartite BMI stratification system (low/normal/high) to systematically investigate its predictive capacity for both immediate surgical outcomes and longitudinal survival parameters in resected PDAC patients. We present this article in accordance with the STROBE reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1022/rc).


Methods

Patients

Patients who underwent pancreatic resection for PDAC from January 2017 to December 2023 at five medical institutions in China were enrolled into this retrospective study. Subsequent exclusion criteria comprised: (I) pediatric populations (<18 years); (II) systemic inflammatory conditions evidenced by either clinical manifestations (fever, leukocytosis) or biochemical markers (C-reactive protein >10 mg/L, erythrocyte sedimentation rate >20 mm/h); (III) unavailable preoperative anthropometric data; (IV) history of major upper abdominal surgery including hepatobiliary or bariatric procedures; (V) minimally invasive surgical approaches; and (VI) incomplete postoperative follow-up documentation. All cases required histopathological confirmation of PDAC through standardized surgical specimen examination protocols. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the ethics committees of all participating centers: Shanghai Changzheng Hospital (No. [registration number]); Lishui Municipal Central Hospital (No. [registration number]); Changshu First People Hospital (No. [registration number]); People’s Hospital of Haimen City (No. [registration number]); and Lu’an People’s Hospital of Anhui Province (No. [registration number]). Written informed consent was obtained from all enrolled participants.

Data acquisition and variables

Baseline data were retrospectively extracted from electronic medical records. Demographic variables comprised sex, age at surgery, ASA physical status, BMI, co-morbidities, Eastern Cooperative Oncology Group (ECOG) performance status, smoking history, and alcohol consumption. BMI was calculated as body weight (kg) divided by height squared (m2) (kg/m2). In addition, BMI was calculated using height and body weight measured at the time of hospital admission for the planned pancreatic resection (immediately preoperatively). Based on World Health Organization (WHO) criteria (17), patients were categorized into three groups: low-BMI (BMI <18.5 kg/m2), normal-BMI (BMI 18.5–25.0 kg/m2), and high-BMI (BMI >25.0 kg/m2). Co-morbid illnesses included hypertension, diabetes mellitus, chronic obstructive pulmonary disease, cardiovascular disease, and renal dysfunction. Preoperative laboratory parameters—assessed within one week prior to surgery—consisted of hemoglobin, platelet count, international normalized ratio (INR), total bilirubin, serum creatinine, alanine aminotransferase (ALT), aspartate transaminase (AST), albumin, and CA19-9. Treatment-related variables encompassed neoadjuvant chemotherapy and preoperative biliary drainage. Clinicopathological characteristics were evaluated, including macroscopic vascular invasion, maximum tumor diameter, histological differentiation, perineural invasion, and pathological staging. Intraoperative variables recorded were blood transfusion volume, estimated blood loss, and operative duration.

Postoperative complications

Postoperative mortality was defined as death occurring within 90 days of surgery or during the initial hospitalization period. Postoperative morbidity encompassed complications arising within 30 days after surgery, which were stratified according to severity using the Clavien-Dindo classification system (18). Minor morbidity (Clavien-Dindo grades I–II) represented non-life-threatening events requiring minimal intervention, whereas major morbidity (grades III–V) involved life-threatening conditions necessitating invasive procedures or intensive care. Specific complications following pancreatic resection were defined using internationally recognized criteria. Postoperative pancreatic fistula (POPF) and clinically relevant POPF (CR-POPF) were diagnosed based on the International Study Group of Pancreatic Surgery (ISGPS) guidelines. CR-POPF included grade B (requiring therapeutic adjustments) and grade C (resulting in organ failure or mortality) (19). Delayed gastric emptying (DGE) was identified per ISGPS criteria as nasogastric tube retention beyond 7 days, tube reinsertion after postoperative day (POD) 7, or inability to resume solid food intake by POD 14 (20). Postpancreatectomy hemorrhage (PPH) required a postoperative hemoglobin drop >3 g/dL from baseline, accompanied by blood transfusion, radiological embolization, or surgical reintervention (21). Chyle leak was confirmed by milky drain output (triglyceride ≥110 mg/dL) occurring on or after POD 3 (22). Surgical site infection (SSI) included superficial or deep incisional infections diagnosed within 30 days postoperatively (23). Biliary leakage was defined as drain fluid bilirubin exceeding threefold serum levels after POD 3 or requiring intervention for biliary peritonitis (24). Additional complications comprised pleural effusion/ascites requiring diuretics or drainage, hepatic insufficiency, pneumonia, acute kidney injury, urinary tract infections, and major cardiocerebrovascular events.

Patient follow-up

Patients underwent standardized postoperative surveillance across participating institutions, with recurrence monitoring comprising physical examinations, serum CA19-9 assessments, and abdominal imaging [ultrasonography or contrast-enhanced computed tomography (CT), magnetic resonance imaging (MRI)] conducted every 2 months during the initial 6-month period, every 3 months for the subsequent 18 months, and biannually thereafter. Suspicion of recurrence or distant metastasis triggered advanced diagnostic evaluations, including cross-sectional imaging (CT/MRI), angiography, bone scintigraphy, or positron emission tomography (PET)-CT. Radiologically confirmed recurrence was defined by newly identified intra- or extra-pancreatic lesions demonstrating PDAC-specific enhancement patterns on imaging, with or without concurrent serum CA19-9 elevation. Survival metrics were calculated as follows: OS spanned from the date of resection to death from any cause or last follow-up contact, while recurrence-free survival (RFS) extended from surgery to either histologically/radiologically confirmed recurrence or censoring at death/last follow-up for recurrence-free cases. The study database was locked for final analysis on December 31, 2024.

Statistical analysis

Baseline patient characteristics were summarized as counts and proportions for categorical variables and medians with ranges or means ± standard deviations for continuous parameters. Continuous variables were analyzed using Student’s t-test or Mann-Whitney U test based on distribution normality, while categorical variables were assessed through Chi-squared or Fisher’s exact tests as appropriate. Study variables were selected to evaluate their association with postoperative outcomes following pancreatic resection for PDAC, informed by established prognostic factors identified in prior literature. Thresholds for continuous variables were derived from clinically validated thresholds reported in existing studies. The postoperative outcomes were compared among the low-BMI, high-BMI, and normal-BMI group. Variables demonstrating univariate associations (P<0.10) underwent multivariable analysis via logistic regression for morbidity outcomes or Cox proportional hazards regression for survival endpoints, with all statistical tests being two-tailed and significance defined at P<0.05. Analyses were performed using IBM SPSS Statistics v25.0 (Armonk, NY, USA).


Results

Clinical and pathological characteristics

A total of 649 patients underwent pancreatic resection for PDAC during the study period, with 597 meeting the inclusion criteria after exclusions. The final cohort comprised 350 males (58.6%) and 247 females (41.4%), with a median age of 67 years (range, 30–91 years). Using BMI cut-off values of 18.5 and 25.0 kg/m2, patients were stratified into low-BMI (n=69, 11.6%), normal-BMI (n=400, 67.0%), and high-BMI (n=128, 21.4%) groups. Baseline demographic, clinical, and pathological characteristics are detailed in Table 1. Notably, the three BMI groups showed comparable distributions of age, sex, ASA scores, ECOG performance status, preoperative therapies, most laboratory parameters, tumor pathology features, and operative characteristics. Two exceptions emerged: The low-BMI group exhibited significantly lower preoperative hemoglobin levels compared to the normal-BMI group (P=0.003). Conversely, the high-BMI group demonstrated greater intraoperative blood loss (61.7% vs. 49.5%, P=0.01) and longer operative duration (P=0.007) relative to the normal-BMI group.

Table 1

Comparisons of patients’ baseline characteristics and operative variables among low-BMI, normal-BMI, and high-BMI group

Variables Total (N=597) Low-BMI group (N=69) Normal-BMI group (N=400) High-BMI group (N=128) P value
Low-BMI vs. normal-BMI High-BMI vs. normal-BMI
Age, years 66.6±9.4 67.3±11.0 66.7±9.2 64.9±9.0 0.96 0.059
Sex
   Male 350 (58.6) 37 (53.6) 231 (57.8) 82 (64.1) 0.52 0.20
   Female 247 (41.4) 32 (46.4) 169 (42.3) 46 (35.9)
ASA score
   ≤2 281 (47.1) 30 (43.5) 194 (48.5) 57 (44.5) 0.44 0.43
   >2 316 (52.9) 39 (56.5) 226 (51.5) 71 (55.5)
BMI, kg/m2 22.5±2.9 17.8±1.1 22.1±1.6 26.4±1.4 <0.001 <0.001
Co-morbid illness 281 (47.1) 38 (55.1) 187 (46.8) 56 (44.1) 0.20 0.60
Cigarette smoking 160 (26.8) 16 (23.2) 106 (26.5) 38 (29.7) 0.56 0.48
Alcohol drinking 132 (22.1) 16 (23.2) 91 (22.8) 25 (19.5) 0.93 0.44
ECOG performance status
   0 124 (20.8) 11 (15.9) 86 (21.5) 27 (21.1) 0.29 0.92
   1–2 473 (79.2) 58 (84.1) 314 (78.5) 101 (78.9)
Neoadjuvant chemotherapy 36 (6.0) 4 (5.8) 25 (6.3) 7 (5.5) 0.88 0.74
Preoperative hemoglobin level, g/L 126.2±18.0 119.0±17.7 126.4±17.7 129.4±18.2 0.003 0.18
Preoperative platelets level, ×109/L 208.0±78.6 224.9±97.0 202.5±72.8 216.0±83.7 0.055 0.17
Preoperative INR 1.02±0.09 1.03±0.07 1.02±0.09 1.03±0.10 0.44 0.55
Preoperative total bilirubin, µmol/L 58.2±77.8 69.4±90.9 57.1±77.5 56.1±71.3 0.39 0.99
Preoperative creatinine level, µmol/L 65.2±19.3 64.5±23.7 65.1±18.4 66.2±19.9 0.96 0.80
Preoperative ALT, U/L 92.3±141.6 81.9±120.8 92.3±144.9 98.0±142.1 0.81 0.90
Preoperative AST, U/L 61.7±88.6 61.0±88.4 63.5±95.3 56.2±63.7 0.96 0.65
Preoperative albumin, g/L 40.1±4.6 39.7±4.5 40.2±4.6 40.2±4.6 0.70 0.99
Maximum tumor size, cm 3.6±1.7 3.7±1.8 3.5±1.7 3.5±1.7 0.69 0.99
   ≤4 429 (71.9) 50 (72.5) 285 (71.3) 94 (73.4) 0.83 0.63
   >4 168 (28.1) 19 (27.5) 115 (28.1) 34 (26.6)
Macroscopic vascular invasion 139 (23.3) 21 (30.4) 85 (21.3) 33 (25.8) 0.09 0.28
Intraoperative blood loss, mL 500 [10–5,000] 400 [50–2,600] 400 [10–3,000] 500 [10–5,000] 0.46 0.95
   ≤400 287 (48.1) 36 (52.2) 202 (50.5) 49 (38.3) 0.79 0.01
   >400 310 (51.9) 33 (47.8) 198 (49.5) 79 (61.7)
Intraoperative blood transfusion 264 (44.2) 36 (52.2) 173 (43.3) 55 (43.0) 0.17 0.95
Operation time, min 218.2±75.6 214.8±80.3 213.2±74.0 235.5±75.9 0.98 0.007

Data are presented as mean ± standard deviation, median [range] or n (%). , co-morbid illnesses include hypertension, diabetes mellitus, cardiovascular disease, chronic obstructive pulmonary disease, and renal dysfunction. ALT, alanine aminotransferase; ASA, American Society of Anesthesiologists; AST, aspartate transaminase; BMI, body mass index; ECOG, Eastern Cooperative Oncology Group; INR, international normalized ratio.

To specifically evaluate the impact of BMI on long-term survival outcomes, we excluded 15 patients who died during the perioperative period (≤90 days postoperatively). The remaining 582 patients formed the survival analysis cohort, with baseline characteristics presented in Table 2.

Table 2

Comparisons of patients’ baseline characteristics and operative variables among low-BMI, normal-BMI, and high-BMI group

Variables Total (N=582) Low-BMI group (N=65) Normal-BMI group (N=395) High-BMI group (N=122) P value
Low-BMI vs. normal-BMI High-BMI vs. normal-BMI
Age, years 66.5±9.3 67.1±10.9 66.9±9.1 65.0±9.1 0.96 0.09
Sex
   Male 340 (58.4) 36 (55.4) 227 (57.8) 77 (64.1) 0.75 0.26
   Female 247 (41.4) 29 (44.6) 168 (42.5) 45 (36.9)
ASA score
   ≤2 281 (47.1) 27 (43.5) 191 (48.5) 54 (44.5) 0.38 0.21
   >2 316 (52.9) 38 (56.5) 204 (51.5) 68 (55.5)
BMI, kg/m2 22.5±2.9 17.7±1.1 22.1±1.6 26.5±1.4 <0.001 <0.001
Co-morbid illness 272 (46.8) 35 (53.8) 184 (46.6) 53 (43.8) 0.27 0.59
Cigarette smoking 158 (27.1) 16 (24.6) 105 (26.6) 37 (30.3) 0.73 0.41
Alcohol drinking 130 (22.3) 16 (24.6) 90 (22.8) 24 (19.7) 0.74 0.46
ECOG performance status
   0 121 (20.8) 10 (15.4) 85 (21.5) 26 (21.3) 0.26 0.96
   1–2 461 (79.2) 55 (84.6) 310 (78.5) 96 (78.7)
Neoadjuvant chemotherapy 32 (5.5) 4 (6.2) 23 (5.8) 5 (4.1) 0.91 0.46
Preoperative hemoglobin level, g/L 126.2±18.1 119.0±18.2 126.4±17.7 129.4±18.4 0.005 0.19
Preoperative platelets level, ×109/L 208.3±78.3 226.5±99.4 202.7±73.0 216.6±80.8 0.045 0.16
Preoperative INR 1.02±0.09 1.03±0.07 1.03±0.10 1.02±0.09 0.39 0.35
Preoperative total bilirubin, µmol/L 58.2±77.7 72.4±92.8 56.8±77.2 55.2±69.8 0.24 0.97
Preoperative creatinine level, µmol/L 65.3±19.4 65.2±24.1 64.9±18.3 66.7±20.1 0.99 0.60
Preoperative ALT, U/L 92.0±140.6 83.8±123.6 92.8±145.6 94.1±133.5 0.86 >0.99
Preoperative AST, U/L 61.3±86.5 53.9±57.5 63.9±95.9 56.7±64.3 0.62 0.66
Preoperative albumin, g/L 40.2±4.6 39.8±4.6 40.2±4.6 40.3±4.6 0.75 0.97
Preoperative CA19-9 level, U/mL 456.2 [0–17,628] 239.9 [0.6–9,215] 142.6 [0.6–7,709] 181.1 [0–17,628] 0.29 0.11
Maximum tumor size, cm 3.5±1.7 3.6±1.8 3.5±1.7 3.5±1.7 0.90 >0.99
   ≤4 421 (72.3) 49 (75.4) 283 (71.6) 89 (73.0) 0.53 0.77
   >4 161 (27.7) 16 (24.6) 112 (28.4) 33 (27.0)
Macroscopic vascular invasion 132 (22.7) 20 (30.8) 81 (20.5) 31 (25.4) 0.06 0.25
Microscopic vascular invasion 222 (38.1) 32 (49.2) 140 (35.4) 50 (41.0) 0.03 0.26
Poor differentiation 204 (35.1) 25 (38.5) 129 (32.7) 50 (51.0) 0.35 0.09
Perineural invasion 435 (74.7) 59 (75.4) 286 (72.4) 100 (82.0) 0.61 0.03
TNM stage
   I 238 (12.9) 26 (40.0) 172 (43.7) 40 (32.8) 0.41 0.09
   II 273 (70.8) 28 (43.1) 178 (45.2) 67 (54.9)
   III 70 (15.0) 11 (16.9) 44 (11.2) 15 (12.3)
Intraoperative blood loss 500 [10–5,000] 400 [50–1,800] 400 [10–5,000] 500 [10–5,000] 0.37 >0.99
   ≤400 282 (48.5) 34 (52.3) 201 (50.9) 47 (38.5) 0.83 0.01
   >400 300 (51.5) 31 (47.7) 194 (49.1) 75 (61.5)
Intraoperative blood transfusion 253 (43.5) 34 (52.3) 168 (42.5) 51 (41.8) 0.14 0.88
Operation time, min 216.4±74.1 209.8±72.6 212.4±74.1 232.8±73.4 0.95 0.01

Data are presented as mean ± standard deviation, median [range] or n (%). , co-morbid illnesses include hypertension, diabetes mellitus, cardiovascular disease, chronic obstructive pulmonary disease, and renal dysfunction. ASA, American Society of Anesthesiologists; BMI, body mass index; CA19-9, carbohydrate antigen 19-9; ECOG, Eastern Cooperative Oncology Group; INR, international normalized ratio; ALT, alanine aminotransferase; ALT, alanine aminotransferase; AST, aspartate transaminase.

Comparisons of postoperative outcomes

Comparative analyses of postoperative short-term outcomes across BMI categories are presented in Table 3, while Table 4 and Table 5 detail the univariate and multivariate analyses of postoperative mortality and morbidity following PDAC resection, respectively. Multivariable regression revealed two distinct risk profiles: patients with low BMI showed independent associations with increased postoperative mortality [odds ratio (OR) 4.952, 95% confidence interval (CI) 1.238–19.799, P=0.02] and overall morbidity (OR 2.008, 95% CI: 1.149–3.509, P=0.01) compared to the normal-BMI group. In addition, high BMI independently predicted elevated mortality risk (OR 3.911, 95% CI: 1.134–13.491, P=0.03) and greater morbidity likelihood (OR 1.820, 95% CI: 1.191–2.783, P=0.006).

Table 3

Comparisons of postoperative outcomes in patients with low-BMI, normal-BMI, and high-BMI

Variables Total (N=597) Low-BMI group (N=69) Normal-BMI group (N=400) High-BMI group (N=128) P value
Low-BMI vs. normal-BMI High-BMI vs. normal-BMI
Perioperative mortality 15 (2.5) 4 (5.8) 5 (1.3) 6 (4.7) 0.02 0.02
Postoperative morbidity 282 (47.2) 42 (60.9) 167 (41.8) 73 (57.0) 0.004 0.003
   Minor morbidity (Clavien-Dindo I–II) 206 (34.5) 29 (42.0) 126 (31.5) 51 (39.8)
   Major morbidity (Clavien-Dindo III–V) 76 (12.7) 13 (18.8) 41 (10.3) 22 (17.2) 0.042 0.03
Type of postoperative complications
   Pancreatic fistula 229 (38.4) 31 (44.9) 145 (36.5) 53 (41.4) 0.16 0.29
   Clinically relevant pancreatic fistula (Grade B/C) 43 (8.7) 9 (13.0) 21 (5.3) 13 (10.1) 0.02 0.049
   Postoperative hemorrhage 46 (7.7) 7 (10.1) 27 (6.8) 12 (9.4) 0.25 0.32
   Delayed gastric emptying 207 (31.5) 17 (24.6) 134 (33.5) 47 (36.7) 0.14 0.50
   Chyle leak 106 (17.8) 18 (26.1) 69 (17.3) 19 (14.8) 0.08 0.52
   Intraperitoneal infection 88 (14.7) 14 (20.3) 56 (14.0) 18 (14.1) 0.17 0.98
   Ascites 68 (11.4) 5 (7.2) 49 (12.3) 14 (10.9) 0.23 0.69
   Pleural effusion 79 (13.2) 10 (14.5) 57 (14.2) 13 (10.2) 0.79 0.23
   Surgical site infection 26 (4.4) 6 (8.7) 13 (3.3) 7 (5.5) 0.03 0.27
   Others 26 (4.4) 4 (3.1) 16 (2.7) 6 (3.4) 0.51 0.73
Patients undergoing interventional or endoscopic treatment 32 (5.4) 6 (8.7) 19 (4.8) 7 (5.5) 0.23 0.75
Patients undergoing reoperation 11 (1.8) 2 (2.9) 7 (1.8) 2 (1.6) 0.52 0.88
Postoperative hospital stays (days) 20.4±13.8 20.4±13.9 20.0±13.5 21.7±14.6 0.96 0.42

Data are presented as n (%). , others include hepatic insufficiency, pulmonary infection, renal dysfunction, urinary infection, cardiocerebrovascular accident, and other severe complications. BMI, body mass index.

Table 4

Univariable and multivariable analyses predicting postoperative mortality

Variables Univariable analysis Multivariable analysis
OR (95% CI) P OR (95% CI) P
Age >65 years 1.137 (0.400–3.237) 0.80
Male 0.702 (0.237–2.081) 0.52
ASA score >2 1.710 (0.601–4.865) 0.31
Low-BMI vs. normal-BMI 4.862 (1.272–18.579) 0.02 4.952 (1.238–19.799) 0.02
High-BMI vs. normal-BMI 3.885 (1.165–12.952) 0.02 3.911 (1.134–13.491) 0.03
Co-morbid illness 1.704 (0.599–4.849) 0.31
Cigarette smoking 2.422 (0.541–10.854) 0.24
Alcohol drinking 1.869 (0.417–8.390) 0.41
ECOG performance status 1–2 1.050 (0.292–3.779) 0.94
Neoadjuvant chemotherapy 6.250 (1.885–20.721) 0.003 4.387 (1.201–16.023) 0.02
Preoperative hemoglobin level ≤110 g/L 1.316 (0.292–5.925) 0.72
Preoperative platelets level ≤100×109/L 3.290 (0.705–15.343) 0.13
Preoperative INR >1.10 2.975 (0.387–22.879) 0.29
Preoperative total bilirubin >34 µmol/L 1.146 (0.387–3.397) 0.80
Preoperative creatinine level >111 µmol/L 1.126 (0.495–3.423) 0.56
Preoperative ALT >40 U/L 1.593 (0.538–4.717) 0.40
Preoperative AST >40 U/L 2.539 (0.709–9.097) 0.15
Preoperative albumin ≤35 g/L 1.743 (0.480–6.324) 0.39
Maximum tumor size >4 cm 2.288 (0.916–6.412) 0.09 NS 0.11
Macroscopic vascular invasion 2.983 (1.062–8.379) 0.03 NS 0.34
Intraoperative blood loss >400 mL 1.880 (0.635–5.568) 0.25
Intraoperative blood transfusion 3.576 (1.125–11.362) 0.03 NS 0.28
Operation time >270 min 6.158 (2.148–17.651) 0.001 4.810 (1.604–14.424) 0.005

, those variables found significant at P<0.1 in univariable analyses were entered into multivariable logistic regression analyses. ALT, alanine aminotransferase; ASA, American Society of Anesthesiologists; AST, aspartate transaminase; BMI, body mass index; CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; INR, international normalized ratio; NS, not significant; OR, odds ratio.

Table 5

Univariable and multivariable analyses predicting postoperative morbidity

Variables Univariable analysis Multivariable analysis
OR (95% CI) P OR (95% CI) P
Age >65 years 1.259 (0.910–1.744) 0.16
Male 1.127 (0.814–1.562) 0.47
ASA score >2 1.266 (0.917–1.748) 0.15
Low-BMI vs. normal-BMI 2,170 (1.287–3.660) 0.004 2.008 (1.149–3.509) 0.01
High-BMI vs. normal-BMI 1.852 (1.238–2.769) 0.003 1.820 (1.191–2.783) 0.006
Co-morbid illness 1.041 (0.754–1.437) 0.80
Cigarette smoking 1.547 (1.070–2.236) 0.02 NS 0.18
Alcohol drinking 1.633 (1.099–2.426) 0.01 1.803 (1.180–2.756) 0.006
ECOG performance status 1–2 1.311 (0.879–1.954) 0.18
Neoadjuvant chemotherapy 1.609 (0.813–3.186) 0.17 NS 0.21
Preoperative hemoglobin level ≤110 g/L 2.396 (1.532–3.749) <0.001 1.674 (1.007–2.783) 0.047
Preoperative platelets level ≤100×109/L 1.305 (0.610–2.793) 0.49
Preoperative INR >1.10 1.883 (1.222–2.903) 0.004 NS 0.08
Preoperative total bilirubin >34 µmol/L 1.397 (0.999–1.952) 0.050 NS 0.08
Preoperative creatinine level >111 µmol/L 1.002 (0.401–2.503) >0.99
Preoperative ALT >40 U/L 1.719 (1.240–2.382) 0.001 1.873 (1.112–3.155) 0.01
Preoperative AST >40 U/L 1.570 (1.126–2.187) 0.008 NS 0.84
Preoperative albumin ≤35 g/L 1.446 (0.892–2.346) 0.13
Maximum tumor size >4 cm 1.515 (1.054–2.176) 0.02 1.517 (1.024–2.246) 0.03
Macroscopic vascular invasion 1.421 (0.971–2.080) 0.07 NS 0.43
Intraoperative blood loss 1.565 (1.132–2.164) 0.007 NS 0.37
Intraoperative blood transfusion 2.307 (1.658–3.208) <0.001 1.667 (1.138–2.442) 0.009
Operation time >270 min 2.740 (1.806–4.157) <0.001 2.299 (1.459–3.623) <0.001

, those variables found significant at P<0.1 in univariable analyses were entered into multivariable logistic regression analyses. ALT, alanine aminotransferase; ASA, American Society of Anesthesiologists; AST, aspartate transaminase; BMI, body mass index; CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; INR, international normalized ratio; NS, not significant; OR, odds ratio.

Comparisons of OS and RFS

Kaplan-Meier curves in Figure 1A,1B demonstrate significantly distinct survival patterns among BMI groups, which show that preoperative both low-BMI and high-BMI emerging as independent prognostic indicators of OS (P=0.008 and P<0.001) and RFS (P=0.005 and P<0.001). Subsequent multivariable Cox-regression analyses confirmed these relationships after adjusting for potential confounders: low BMI independently predicted poorer OS [hazard ratio (HR) 1.410, 95% CI: 1.049–1.896, P=0.02] and RFS (HR 1.395, 95% CI: 1.050–1.853, P=0.02), while high BMI showed stronger associations with reduced OS (HR 1.609, 95% CI: 1.274–2.034, P<0.001) and RFS (HR 1.575, 95% CI: 1.249–1.987, P<0.001). Complete univariate and multivariate analysis results are detailed in Table 6 and Table 7.

Figure 1 Overall survival (A) and recurrence-free survival (B) curves comparisons among low-BMI, normal-BMI, and high-BMI groups. BMI, body mass index.

Table 6

Univariable and multivariable analyses predicting overall survival

Variables Univariable analysis Multivariable analysis
HR (95% CI) P HR (95% CI) P
Age >65 years 1.073 (0.886–1.298) 0.47
Male 1.295 (1.067–1.573) 0.009 NS 0.08
ASA score >2 1.072 (0.887–1.295) 0.47
Low-BMI vs. normal-BMI 1.515 (1.133–2.026) 0.005 1.410 (1.049–1.896) 0.023
High-BMI vs. normal-BMI 1.694 (1.344–2.136) <0.001 1.609 (1.274–2.034) <0.001
Co-morbid illness 1.191 (0.985–1.441) 0.07 1.285 (1.059–1.559) 0.01
Cigarette smoking 1.122 (0.906–1.389) 0.29
Alcohol drinking 1.161 (0.925–1.456) 0.19
ECOG performance status 1–2 1.186 (0.940–1.497) 0.15
Neoadjuvant chemotherapy 1.057 (0.694–1.609) 0.79
Preoperative hemoglobin level ≤110 g/L 1.419 (0.331–3.205) 0.96
Preoperative platelets level ≤100×109/L 1.417 (0.922–2.178) 0.11
Preoperative INR >1.10 1.082 (0.850–1.377) 0.52
Preoperative total bilirubin >34 µmol/L 1.060 (0.817–1.291) 0.56
Preoperative creatinine level >111 µmol/L 1.158 (0.692–1.939) 0.57
Preoperative ALT >40 U/L 1.139 (0.942–1.377) 0.17
Preoperative AST >40 U/L 1.094 (0.902–1.328) 0.36
Preoperative albumin ≤35 g/L 1.177 (0.878–1.577) 0.27
Preoperative CA19-9 level 1.120 (0.937–1.588) 0.14
Maximum tumor size >4 cm 1.284 (1.048–1.573) 0.01 1.248 (1.017–1.532) 0.03
Macroscopic vascular invasion 1.647 (1.327–2.043) <0.001 NS 0.41
Microscopic vascular invasion 1.539 (1.272–1.861) <0.001 1.383 (1.140–1.679) 0.001
Poor differentiation 1.440 (1.181–1.756) <0.001 1.380 (1.127–1.690) 0.002
Perineural invasion 1.389 (1.107–1.742) 0.004 NS 0.24
Intraoperative blood loss >400 mL 1.430 (1.182–1.730) <0.001 NS 0.78
Intraoperative blood transfusion 1.503 (1.242–1.819) <0.001 1.440 (1.186–1.749) <0.001
Operation time >270 min 1.205 (0.952–1.527) 0.12

, those variables found significant at P<0.1 in univariable analyses were entered into multivariable logistic regression analyses. ALT, alanine aminotransferase; ASA, American Society of Anesthesiologists; AST, aspartate transaminase; BMI, body mass index; CA19-9, carbohydrate antigen 19-9; CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; HR, hazard ratio; INR, international normalized ratio; NS, not significant.

Table 7

Univariable and multivariable analyses predicting recurrence-free survival

Variables Univariable analysis Multivariable analysis
HR (95% CI) P HR (95% CI) P
Age >65 years 1.049 (0.872–1.261) 0.61
Male 1.295 (1.067–1.573) 0.03 NS 0.21
ASA score >2 1.032 (0.859–1.239) 0.73
Low-BMI vs. normal-BMI 1.511 (1.142–2.001) 0.004 1.395 (1.050–1.853) 0.02
High-BMI vs. normal-BMI 1.632 (1.298–2.050) <0.001 1.575 (1.249–1.987) <0.001
Co-morbid illness 1.183 (0.984–1.421) 0.07 1.220 (1.012–1.471) 0.03
Cigarette smoking 1.130 (0.922–1.385) 0.23
Alcohol drinking 1.165 (0.37–1.448) 0.17
ECOG performance status 1–2 1.151 (0.919–1.443) 0.2
Neoadjuvant chemotherapy 1.057 (0.694–1.609) 0.797
Preoperative hemoglobin level ≤110 g/L 1.232 (0.961–1.578) 0.09 NS 0.48
Preoperative platelets level ≤100×109/L 1.409 (0.926–2.144) 0.11
Preoperative INR >1.10 1.203 (0.949–1.524) 0.12
Preoperative total bilirubin >34 µmol/L 1.046 (0.865–1.265) 0.64
Preoperative creatinine level >111 µmol/L 1.116 (0.667–1.868) 0.67
Preoperative ALT >40 U/L 1.024 (0.852–1.231) 0.79
Preoperative AST >40 U/L 1.039 (0.861–1.254) 0.68
Preoperative albumin ≤35 g/L 1.130 (0.856–1.491) 0.38
Preoperative CA19-9 level >1,000 U/mL 1.266 (0.980–1.637) 0.07 NS 0.06
Maximum tumor size >4 cm 1.211 (0.992–1.479) 0.06 NS 0.08
Macroscopic vascular invasion 1.463 (1.182–1.811) <0.001 NS 0.64
Microscopic vascular invasion 1.394 (1.158–1.678) <0.001 NS 0.09
Poor differentiation 1.440 (1.181–1.756) <0.001 1.355 (1.115–1.645) 0.002
Perineural invasion 1.536 (1.224–1.928) <0.001 1.369 (1.081–1.733) 0.009
Intraoperative blood loss >400ml 1.394 (1.160–1.675) <0.001 NS 0.91
Intraoperative blood transfusion 1.462 (1.216–1.759) <0.001 1.468 (1.217–1.771) <0.001
Operation time >270 min 1.032 (0.818–1.300) 0.79

, those variables found significant at P<0.1 in univariable analyses were entered into multivariable logistic regression analyses. ALT, alanine aminotransferase; ASA, American Society of Anesthesiologists; AST, aspartate transaminase; BMI, body mass index; CA19-9, carbohydrate antigen 19-9; CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; HR, hazard ratio; INR, international normalized ratio; NS, not significant.


Discussion

This multicenter cohort study investigated preoperative BMI associations with perioperative and long-term outcomes in patients undergoing PDAC resection in a large sample size. The analysis revealed a U-shaped relationship between BMI and clinical prognosis following pancreatic resection for PDAC. In addition, both high-BMI and low-BMI extremes emerged as independent risk factors for CR-POPF, and low-BMI group demonstrated significantly higher SSI rates. These findings establish preoperative BMI as an objective, readily accessible prognostic marker that may guide (I) preoperative nutritional optimization, (II) surgical risk stratification, and (III) personalized postoperative monitoring protocols in PDAC resection candidates.

Overweight and obesity are defined as abnormal adipose tissue accumulation conferring health risks, with 2019 data attributing 5 million noncommunicable disease deaths annually to supraoptimal BMI levels. Global prevalence has escalated dramatically across all demographics—pediatric obesity rates quadrupled from 2% [1990] to 8% [2022] in children aged 5–19 years, while adult obesity prevalence surged from 7% to 16% during this period. Notably, this public health crisis has transitioned from predominantly high-income nations to middle-income countries, where some now demonstrate the world’s highest obesity burdens (WHO, n.d.). This metabolic pandemic substantially elevates population risks for diabetes mellitus, cardiovascular diseases, and obesity-associated malignancies (colorectal, hepatic, and breast carcinomas) (25-28). Emerging evidence suggests potential oncologic implications in PDAC, though current research presents conflicting data regarding obesity’s prognostic significance in pancreatic cancer outcomes.

Emerging evidence reveals complex obesity-survival relationships in pancreatic oncology. Balentine et al. identified nonlinear associations between visceral adiposity and mortality risk, with second-quartile patients exhibiting quadrupled mortality likelihood versus the leanest cohort (29). While Mathur et al. demonstrated comparable perioperative outcomes across BMI strata, they observed significantly reduced survival in obese patients post-pancreatoduodenectomy (30). This contrasts with Benns et al.’s (31) null findings comparing obese versus non-obese surgical outcomes (19.8 vs. 23.5 months OS, P=0.46), though aligns with Fleming et al.’s (32) report of 95% survival reduction in severe obesity (BMI >35 kg/m2, P=0.01). Prognostic effect of preoperative obesity on survival after operation needed further investigation. Therefore, we conducted the multicenter study to identify the prognostic role of BMI on morbidity and survival from PDAC. This is a latest cohort, representing the status of the Asian population in recent years. Results indicated that obesity in adulthood was associated with a significantly worse OS (HR 1.609, 95% CI: 1.274–2.034, P<0.001) and RFS (HR 1.575, 95% CI: 1.249–1.987, P<0.001), suggesting that obesity may be a potential important prognostic factor for PDAC.

The mechanistic relationship between adult obesity and reduced post-diagnosis survival in pancreatic cancer remains incompletely understood. While rapid disease progression limits the explanatory power of chronic obesity-related comorbidities like cardiovascular disorders, emerging evidence implicates insulin resistance as a pivotal mediator linking adiposity to both decreased OS and heightened disease burden (33,34). Obesity-driven metabolic dysregulation elevates circulating levels of insulin resistance-promoting factors including glycerol, non-esterified fatty acids, proinflammatory cytokines (e.g., TNF-α, IL-6), and adipokines, which collectively impair glucose homeostasis (35,36). This metabolic perturbation triggers compensatory hyperinsulinemia through pancreatic β-cell overactivation, creating a protumorigenic milieu via insulin/IGF-1 receptor crosstalk. Elevated IGF-1 levels subsequently stimulate cancer cell proliferation while inhibiting apoptosis through PI3K/AKT pathway activation. Concurrently, obesity-induced DNA repair dysfunction, leptin-dominated adipokine imbalance, and chronic inflammation synergistically promote oncogenesis through enhanced genomic instability, vascular endothelial growth factor (VEGF)-mediated angiogenesis, and immune evasion mechanisms, ultimately culminating in accelerated disease progression and mortality (37,38).

Preoperative low BMI was independently associated with increased postoperative mortality and overall morbidity following pancreatic resection for PDAC. This association may be mechanistically linked to the established correlation between low BMI and sarcopenia/hypoalbuminemia, which reflect impaired immune competence and nutritional deficiencies that compromise surgical stress adaptation (39-42). Our cohort further demonstrated significantly reduced hemoglobin levels in low-BMI patients, suggesting anemia of chronic disease as a potential malnutrition marker contributing to poor outcomes. The heightened surgical vulnerability in this population aligns with broader surgical literature demonstrating elevated SSI risks among low-BMI patients (43,44), a pattern replicated in our findings. These collective data suggest that the nutritional and physiological deficits inherent to low BMI create a perioperative risk profile requiring targeted prehabilitation strategies.

Pancreatic resection remains associated with substantial postoperative morbidity, including technically mediated complications such as anastomotic leakage, intra-abdominal hemorrhage, and infectious sequelae, as well as systemic manifestations like gastrointestinal bleeding, all contributing to mortality risk. The surgical stress response exacerbates preoperative malnutrition and progressive weight loss, which are independently correlated with adverse outcomes. Conversely, obesity confers distinct perioperative vulnerabilities, elevating risks of intraoperative hemorrhage, SSIs, thromboembolic events (deep venous thrombosis/pulmonary embolism), and metabolic derangements. Of these complications, POPF represents the most consequential technical failure, occurring in up to 30% of cases even at high-volume centers (45,46). Given that CR-POPF severity directly correlates with prolonged hospitalization, adjuvant therapy delays, and survival impairment, preoperative BMI evaluation may enhance individualized risk-benefit assessments and inform shared decision-making (45). Our data demonstrate a bimodal risk association, with both low BMI and high BMI independently predicting CR-POPF development following pancreatic resection of patients with PDAC. This U-shaped risk profile positions BMI as an accessible preoperative biomarker for dual clinical utility to stratify patients into risk-adapted surgical pathways (e.g., reinforced anastomotic techniques or prophylactic drain placement) and to guide targeted nutritional optimization protocols aimed at mitigating sarcopenia or metabolic syndrome.

The present study also has several limitations. First, while leveraging a prospectively maintained database, the retrospective design inherently limits data accuracy and completeness compared to prospective registries with protocol-driven validation processes. Second, although our cohort demonstrated distinctive BMI-related surgical risk patterns, the limited prevalence of obesity (BMI >30 kg/m2 in Western cohorts) and exclusive Chinese derivation restrict generalizability, highlighting the need for international multicenter validation of BMI-associated complication risks. Third, preoperative nutritional status metrics prove particularly problematic given the characteristic cancer-associated cachexia in pancreatic malignancies or the treatment of neoadjuvant therapy, potentially confounding BMI interpretation through fluid retention and tumor-induced metabolic alterations.

In conclusion, this large-scale multicenter study demonstrates that the BMI can serve as an independent predictor of postoperative short-term and long-term outcomes in patients undergoing pancreatic resection for PDAC. These findings necessitate BMI-adapted treatment algorithms incorporating prehabilitation protocols for underweight patients and metabolic optimization strategies for obese individuals. Future guidelines should mandate preoperative nutritional optimization and establish BMI-specific surveillance intervals through multidisciplinary collaboration with nutritional oncology specialists.


Acknowledgments

None.


Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1022/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1022/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1022/prf

Funding: This study was supported by grants from the Naval Medical University Research Physician Training Project (V1.0: 20170206) and the Young Scientists Fund of the National Natural Science Foundation of China (grant No. 82303330).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-1-1022/coif). The 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. The study was approved by the ethics committees of all participating centers: Shanghai Changzheng Hospital (No. [registration number]); Lishui Municipal Central Hospital (No. [registration number]); Changshu First People Hospital (No. [registration number]); People’s Hospital of Haimen City (No. [registration number]); and Lu’an People’s Hospital of Anhui Province (No. [registration number]). Written informed consent was obtained from all enrolled participants.

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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Cite this article as: Li J, Niu T, Shi L, Deng X, Mao X, Yang G, Liang X, Ji M, Tang L, Chen D, Liu A, Lv X, Hu L, Wang X, Wu W, Shao C. Impact of preoperative body weight on short-term and long-term prognosis after pancreatic resection for pancreatic ductal adenocarcinoma: a multicenter study. J Gastrointest Oncol 2026;17(2):91. doi: 10.21037/jgo-2025-1-1022

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