Abstract
Objective:
To evaluate the association between preoperative malnutrition and long-term outcomes in patients with pancreatic head cancer who underwent curative pancreatoduodenectomy (PD).
Methods:
From 2004 to 2018, 228 consecutive patients who underwent curative PD for pancreatic ductal adenocarcinoma were included. Preoperative malnutrition was defined by the Global Leadership Initiative in Malnutrition criteria. It is based on both phenotypic criteria (weight loss, low body mass index, and reduced muscle mass) and etiologic criteria (reduced intake or assimilation and inflammation).
Results:
Seventy-five (32.9%) of 228 patients were classified as suffering from malnutrition. Preoperative malnutrition was associated with an increased risk of estimated blood loss (mL) (816.7 ± 875.2 vs 593.1 ± 489.9, P = 0.015) and longer hospital stay (days) (27.3 ± 15.7 vs 22.9 ± 17.7, P = 0.045). The median follow-up period was 24.5 months. The malnutrition group had poor overall survival compared with “without (WO)-malnutrition” group (P = 0.001) at 1 year (66.3% vs 81.3%), 3 years (18.0% vs 51.8%), and 5 years (12.0% vs 39.3%). The malnutrition group showed poor disease-free survival and cancer-specific survival compared with WO-malnutrition group (P = 0.001) at 1 year (38.9% vs 66.7%) and (69.0% vs 88.7%), 3 years (11.5% vs 45.1%) and (21.1% vs 61.6%), and 5 years (11.5% vs 37.3%) and (14.1% vs 51.2%). In multivariate analysis, the preoperative malnutrition was found to be the predictor of poor prognosis (harzard ratio = 2.29, 95% confidence interval = 1.60–3.29, P = 0.001).
Conclusions:
Preoperative malnutrition is associated with poor prognosis in patients who underwent curative PD for pancreatic head cancer.
Mini-abstract: Preoperative malnutrition occurs frequently in the patient with pancreatic head cancer. In this study, preoperative malnutrition has been shown to be associated with poor long-term survival outcomes.
INTRODUCTION
Despite recent improvements in operative techniques and advances in adjuvant treatment, the patients with pancreatic cancer have a poor prognosis.1,2 The pancreatic cancer may be associated with malnutrition due to poor oral intake, abdominal pain, indigestion, and malabsorption.3 The incidence of malnutrition in pancreatic cancer at the time of diagnosis is reported from 65% to 80% depending on the methods used to identify malnutrition.4,5
Preoperative malnutrition is associated with many adverse clinical outcomes, including a longer hospital stay, increased morbidity, and increased hospital costs.6 In addition, the preoperative malnutrition is associated with poor survival in patients undergoing surgery for malignancy.7 Reports regarding the association between malnutrition and the survival rate for pancreatic cancer are scarce and focused mainly on advanced stage.8 Therefore, the study on the impact of preoperative malnutrition on survival in pancreatic head cancer with curative resection would be beneficial.
Although the nutritional screening and assessment are important, there are few widely accepted guidelines regarding the diagnostic criteria for malnutrition. Recently, the Global Leadership Initiative in Malnutrition (GLIM) group published a new consensus regarding the definition of malnutrition.9 The criteria are based on both phenotypic criteria (weight loss, low body mass index [BMI], and reduced muscle mass) and etiologic criteria (reduced food intake or assimilation and inflammation).9
In the present study, we evaluate the impact of preoperative malnutrition, using the GLIM criteria, on long-term outcomes in patients with pancreatic head cancer who underwent curative pancreatoduodenectomy (PD).
MATERIAL AND METHODS
Patients
All patients who underwent curative PD for pancreatic head cancer between January 2004 to December 2018 were analyzed in this study. The data included all cases of pathologically confirmed ductal adenocarcinoma. Patients with palliative resection and distant metastasis were excluded. In addition, the patients without quantified data of weight at admission and 6 months before surgery were excluded. The protocol of this retrospective study was approved by the institutional review board of the Seoul National University Bundang Hospital, South Korea (Approval No. B-2004-604-113).
Variables
Preoperative malnutrition was defined by the GLIM criteria that were based on the top 5 ranked criteria that included 3 phenotypic criteria (nonvolitional weight loss, low BMI, and reduced muscle mass) and 2 etiologic criteria (reduced food intake or assimilation and inflammation or disease burden).9 Malnutrition was diagnosed when a patient met at least 1 phenotypic and 1 etiologic criterion. According to the Asia-Pacific guidelines, a patient is defined as having low BMI if the BMI is less than 18.5 kg/m2.10,11 Patients who did not meet the malnutrition criteria were defined as “without (WO)-malnutrition” group.
The demographics, operative outcomes, pathological findings, and oncologic outcomes were compared between the malnutrition and WO-malnutrition groups. Stages were defined according to the 8th edition of the American Joint Committee on Cancer. Patients who had a postoperative complication within 30 days after surgery were graded using the Clavien–Dindo classification.12 Major complications were defined as equivalent to the Clavien–Dindo grade III or higher. Readmission was defined as hospitalization within 3 months after discharge.
Postoperative follow-up including physical exam, abdominal computed tomography scans, and tumor markers were performed every 3–6 months for 2 years after surgery, then in 6-month intervals for 5 years, and then 12-month intervals thereafter. Overall survival (OS) was defined as the duration from primary surgery to the date of death regardless of cause. Disease-free survival (DFS) was defined as the time interval from primary surgery to the first documented detection of recurrence during regular follow-up. Cancer-specific survival (CSS) was defined as the duration from the date of diagnosis until death due to cancer.
Statistics
Statistical analysis was processed using the SPSS software package for Windows, Version 22 (IBM Corporation, Armonk, NY). The demographic and perioperative characteristics were summarized using descriptive analyses, and all qualitative values are presented as mean ± SD unless stated otherwise. The Student t test or Mann–Whitney U test was used for continuous variables, whereas the and Pearson χ2 test was used for categorical variables. All P values <0.05 were considered statistically significant. The Kaplan–Meier estimator was used for survival estimation and the log-rank test was used for survival comparison. Cox proportional hazard regression modeling was conducted to examine the strength of association between the covariates and survival time. All analyses were performed using a 2-tailed a-value of 0.05, and either P < 0.05 or the 95% confidence interval (CI) was considered to indicate a statistically significant value.
RESULTS
Patients Characteristics
A total of 228 patients were included in this study and their demographics are summarized in Table 1. Seventy-five patients (32.9%) were diagnosed with malnutrition at the time of admission. There were no significant differences in age, gender, Eastern Cooperative Oncology Group performance status, and hypertension between the malnutrition and WO-malnutrition groups. The BMI is similar between the two groups (22.1 ± 2.72 vs 22.8 ± 2.58, P = 0.075). The proportion of patients with diabetes mellitus (52.0% vs 37.9%, P = 0.001) was significantly higher in the malnutrition group. Jaundice (61.3% vs 43.8%, P = 0.016) was significantly higher in malnutrition group. Although, the mean serum albumin level was similar between the groups (P = 0.351), the proportion of patients with hypoalbuminemia (<3.5 g/dL) was significantly higher in malnutrition group than WO-malnutrition group (22.7% vs 14.4%, P = 0.036). Serum carcinoembryonic antigen was similar in the 2 groups (P = 0.332), but the preoperative serum carbohydrate antigen 19-9 was significantly higher in the malnutrition group (555.5 ± 1078.4 vs 403.1 ± 911.5, P = 0.007).
TABLE 1.
Demographics of the Patients
| Variables | Malnutrition (N = 75) | WO-Malnutrition (N = 153) | P |
|---|---|---|---|
| Age (yr) | 64.8 ± 11.8 | 64.7 ± 10.0 | 0.891 |
| Gender, N (%) | |||
| Male | 38 (50.7) | 83 (54.2) | 0.672 |
| Female | 37 (49.3) | 70 (45.8) | |
| Body mass index (kg/m2) | 22.1 ± 2.72 | 22.8 ± 2.58 | 0.075 |
| ASA, N (%) | |||
| 1 | 13 (17.3) | 27 (17.6) | 0.856 |
| 2 | 53 (70.7) | 105 (68.6) | |
| 3 | 9 (12.0) | 21 (13.7) | |
| ECOG performance status, N (%) | |||
| 0 | 53 (70.7) | 114 (74.5) | 0.53 |
| 1 | 22 (29.3) | 39 (25.5) | |
| Diabetes mellitus, N (%) | |||
| Yes | 39 (52.0) | 58 (37.9) | 0.047 |
| No | 36 (48.0) | 95 (62.1) | |
| Hypertension, N (%) | |||
| Yes | 37 (49.3) | 67 (43.8) | 0.48 |
| No | 38 (50.7) | 86 (56.2) | |
| Previous abdominal surgery, N (%) | |||
| Yes | 22 (29.3) | 43 (28.1) | 0.877 |
| No | 53 (70.7) | 110 (71.9) | |
| Preoperative jaundice, N (%) | |||
| Yes | 46 (61.3) | 67 (43.8) | 0.016 |
| No | 29 (38.7) | 86 (56.2) | |
| Preoperative albumin (g/dL) | 3.71 ± 0.47 | 3.97 ± 0.51 | 0.351 |
| Preoperative hypoalbuminemia, <3.5 (g/dL), N (%) | 17 (22.7) | 22 (14.4) | 0.036 |
| Preoperative hemoglobin (g/dL) | 12.1 ± 1.69 | 12.7 ± 1.56 | 0.371 |
| Preoperative bilirubin | 7.55 ± 7.17 | 5.16 ± 6.81 | 0.073 |
| Preoperative white blood cells | 7936 ± 8671 | 6201 ± 1973 | 0.02 |
| Preoperative CRP | 1.42 ± 2.37 | 1.55 ± 2.99 | 0.261 |
| Preoperative CEA | 4.21 ± 4.36 | 4.00 ± 7.87 | 0.332 |
| Preoperative CA 19-9 | 555.5 ± 1078.4 | 403.1 ± 911.5 | 0.007 |
All qualitative values are presented as mean ± SD.
ASA indicates American Society of Anesthesiologists; CA 19-9, carbohydrate antigen 19-9; CEA, carcinoembryonic antigen; CRP, C-reactive protein; ECOG, Eastern Cooperative Oncology Group/World Health Organization Performance Status.
Operative Outcomes
Table 2 summarizes the operative outcomes of both groups. The operation time (min) was similar in the 2 groups (P = 0.292), but the estimated blood loss (EBL, mL) (816.7 ± 875.2 vs 593.1 ± 489.9, P = 0.015) was significantly higher in the malnutrition group. The hospital duration (days) (27.3 ± 15.7 vs 22.9 ± 17.7, P = 0.045) was significantly longer in the malnutrition group. Although the overall complication rate was significantly higher in the malnutrition group than that in the WO-malnutrition group (44% vs 37.9%, P = 0.046), the major complication rate was similar (26.7% vs 25%, P = 0.186). The tumor stage was advanced in the malnutrition group (P = 0.046).
TABLE 2.
Perioperative Outcomes
| Variables | Malnutrition (N = 75) | WO-Malnutrition (N = 153) | P |
|---|---|---|---|
| Operation time (min) | 421.4 ± 136.7 | 403.1 ± 116.5 | 0.292 |
| Estimated blood loss (mL) | 816.7 ± 875.2 | 593.1 ± 489.9 | 0.015 |
| Laparoscopy, N (%) | 10 (13.4) | 22 (14.4) | 0.109 |
| Intraoperative transfusion, N (%) | |||
| Yes | 22 (29.3) | 34 (22.2) | 0.065 |
| No | 53 (70.7) | 119 (77.8) | |
| Hospital stay (d) | 27.3 ± 15.7 | 22.9 ± 17.7 | 0.045 |
| Overall complications, N (%) | 33 (44.0) | 58 (37.9) | 0.046 |
| Major complications, N (%) (Clavien–Dindo) | 20 (26.7) | 38 (25.0) | 0.186 |
| Grade IIIA | 15 (20.0) | 31 (20.3) | |
| Grade IIIB | 1 (1.3) | 5 (3.3) | |
| Grade IVA | 2 (2.7) | 0 | |
| Grade IVB | 0 | 1 (0.7) | |
| Grade V | 2 (2.7) | 1 (0.7) | |
| Readmission within 3 mo, N (%) | |||
| Yes | 5 (6.7) | 10 (6.5) | 0.315 |
| No | 70 (93.3) | 143 (93.5) | |
| Tumor size (cm) | 2.97 ± 0.93 | 2.94 ± 1.09 | 0.079 |
| Stage (AJCC 8th) | |||
| IA | 1 (1.3) | 5 (3.3) | 0.046 |
| IB | 0 | 8 (5.2) | |
| IIA | 20 (26.7) | 51 (33.3) | |
| IIB | 52 (69.3) | 84 (54.9) | |
| III | 2 (2.7) | 5 (3.3) | |
All qualitative values are presented as mean ± SD.
AJCC indicates American Joint Committee on Cancer.
Comparison of Long-Term Survival Between Groups
Figure 1 shows the Kaplan–Meier survival curve of OS, DFS, and CSS between the malnutrition and the WO-malnutrition group. The median follow-up period after primary surgery was 24.5 months, during which 125 patients (54.8%) died. About 96 (76.8%) cancer-specific death and 29 (23.2%) noncancer-specific deaths were observed. The malnutrition group had poor OS (P < 0.001) compared with the WO-malnutrition group at 1 year (66.3% vs 81.3%), 3 years (18.0% vs 51.8%), and 5 years (12.0% vs 39.3%). The malnutrition group had poor DFS (P < 0.001) compared with the WO-malnutrition group at 1 year (38.9% vs 66.7%), 3 years (11.5% vs 45.1%), and 5 years (11.5% vs 37.3%). The malnutrition group had poor CSS (P < 0.001) compared with the WO-malnutrition group at 1 year (69.0% vs 88.7%), 3 years (21.1% vs 61.6%), and 5 years (14.1% vs 51.2%).
FIGURE 1.
OS, DFS, and CSS between the malnutrition and the “WO-malnutrition” group. The malnutrition group had poor OS (P < 0.001), DFS (P < 0.001), and CSS (P < 0.001) rates compared with WO-malnutrition group. A, OS; 1 year (66.3% vs 81.3%), 3 years (18.0% vs 51.8%), and 5 years (12.0% vs 39.3%). B, DFS; 1 year (38.9% vs 66.7%), 3 years (11.5% vs 45.1%), and 5 years (11.5% vs 37.3%). C, CSS, 1 year (69.0% vs 88.7%), 3 years (21.1% vs 61.6%), and 5 years (14.1% vs 51.2%).
Figure 2 shows the survival curve of OS, DFS, and CSS between the two groups in Stage II. As most of patients belong to Stage II, we conducted subgroup analyses only with Stages IIA and IIB. In Stage IIA, the malnutrition group had poor OS compared with the WO-malnutrition group at 1 year (70% vs 84.3%), 3 years (22% vs 59.2%), and 5 years (15.2% vs 46.4%). In Stage IIB, the malnutrition group had also poor OS compared with the WO-malnutrition group at 1 year (64.9% vs 77%), 3 years (15.2% vs 41.9%), and 5 years (11.0% vs 30.1%). The malnutrition group had poor DFS compared with the WO-malnutrition group at 1 year (40.1% vs 72.9%), 3 years (13.4% vs 58.2%), and 5 years (13.4% vs 47.2%) in Stage IIA. In Stage IIB, the malnutrition group also had poor DFS compared with the WO-malnutrition group at 1 year (31.7% vs 61.4%), 3 years (11.3% vs 31.4%), and 5 years (11.3% vs 28.5%).
FIGURE 2.
The survival curve of OS and DFS between two groups in Stages IIA and IIB. The malnutrition group had poor survival (OS) (P < 0.001), DFS (P < 0.001), and CSS (P < 0.001) rates than WO-malnutrition group in Stages IIA and IIB. A, OS; Stage IIA, 1/3/5 years (70% vs 84.3%), (22% vs 59.2%), and (15.2% vs 46.4%); Stage IIB, 1/3/5 years (64.9% vs 77%), (15.2% vs 41.9%), and (11.0% vs 30.1%). B, DFS; Stage IIA, 1/3/5 years (40.1% vs 72.9%), (13.4% vs 58.2%), and (13.4% vs 47.2%). Stage IIB, 1/3/5 years (31.7% vs 61.4%), (11.3% vs 31.4%), and (11.3% vs 28.5%). C, CSS; Stage IIA, 1/3/5 years (69.1% vs 86.0%), (20.5% vs 62.5%), and (13.6% vs 58.0%). Stage IIB, 1/3/5 years (67.2% vs 88.1%), (16.9% vs 54.0%), and (16.9% vs 38.8%).
The malnutrition group had poor CSS compared with the WO-malnutrition group at 1 year (69.1% vs 86.0%), 3 years (20.5% vs 62.5%), and 5 years (13.6% vs 58.0%) in Stage IIA. In Stage IIB, the malnutrition group had poor CSS compared with the WO-malnutrition group at 1 year (67.2% vs 88.1%), 3 years (16.9% vs 54.0%), and 5 years (16.9% vs 38.8%).
Univariate and Multivariate Analyses of Factors Associated With Survival
Table 3 shows the factors associated with OS, DFS, and CSS in the overall patient group. The univariate analysis revealed that malnutrition, preoperative albumin, EBL, tumor size, and stage correlated with OS. In multivariate analysis, malnutrition (harzard ratio [HR] = 2.29, 95% CI = 1.60–3.29, P = 0.001), preoperative albumin (HR = 0.55, 95% CI = 0.34–0.89, P = 0.016), EBL (HR = 1.83, 95% CI = 1.27–2.68, P = 0.001), and tumor size (HR = 0.57, 95% CI = 0.11–0.87, P = 0.011) were found to be the predictors of poor OS.
TABLE 3.
Univariate and Multivariate Analyses of Factors Associated With Overall Survival, Disease-Free Survival, and Cancer-Specific Survival
| Overall Survival | Disease-Free Survival | Cancer-Specific Survival | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Uni. | Multi. | Uni. | Multi. | Uni. | Multi. | ||||
| Variable | P | HR (95% CI) | P | P | HR (95% CI) | P | P | HR (95% CI) | P |
| Age (yr) (<65 and ≥65) | 0.400 | 0.101 | 0.091 | ||||||
| Male | 0.333 | 0.544 | 0.310 | ||||||
| DM | 0.838 | 0.082 | 0.461 | ||||||
| Mal-N | 0.008 | 2.29 (1.60–3.29) | 0.001 | 0.028 | 1.13 (1.07–1.67) | 0.017 | 0.008 | 1.98 (1.06–1.59) | 0.016 |
| Preop. albumin (<3.5 and ≥3.5 g/dL) | 0.028 | 0.55 (0.34–0.89) | 0.016 | 0.082 | 0.778 | ||||
| Jaundice | 0.975 | 0.382 | 0.658 | ||||||
| Neoadj. CTx | 0.639 | 0.059 | 0.604 | ||||||
| EBL (<500 and ≥500) | 0.025 | 1.83 (1.27–2.68) | 0.001 | 0.018 | 0.86 (0.5–91.23) | 0.861 | 0.032 | 0.98 (0.65–1.51) | 0.948 |
| Cx | 0.332 | 0.715 | 0.770 | ||||||
| Adj. CTx | 0.145 | 0.852 | 0.398 | ||||||
| Tumor size (<3 and ≥3 cm) | 0.001 | 0.58 (0.11–0.87) | 0.011 | 0.196 | 0.001 | 0.51 (0.16–0.57) | 0.001 | ||
| Stage I versus IIA versus IIB versus III | 0.016 | 0.34 (0.11–1.05) | 0.061 | 0.002 | 0.69 (0.55–0.87) | 0.001 | 0.001 | 0.33 (0.20–0.52) | 0.001 |
Adj. indicates adjuvant; CI, confidence interval; CTx., chemotherapy; Cx., complication; DM, diabetes mellitus; HR, harzard ratio; Mal-N, malnutrition; Multi., multivariate analysis; Neoadj., neoadjuvant; Preop., preoperative; Uni., univariate analysis.
In DFS, the malnutrition, EBL, and stage were significant factors in univariate analysis. Malnutrition (HR = 1.13, 95% CI = 1.07–1.67, P = 0.017) and stage (HR = 0.69, 95% CI = 0.55–0.87, P = 0.001) were correlated with poor DFS in multivariate analysis.
In CSS, the malnutrition, EBL, tumor size, and stage were significant factors in univariate analysis. In multivariate analysis, malnutrition (HR = 1.98, 95% CI = 1.06–1.59, P = 0.016), tumor size (HR = 0.51, 95% CI = 0.16–0.57, P = 0.001), and stage (HR = 0.33, 95% CI = 0.20–0.52, P = 0.001) were found to be the predictive factors for poor CSS.
DISCUSSION
The prevalence of preoperative malnutrition in our study cohort was 32.9% at the time of admission. Patients with malnutrition were associated with a prolonged length of hospital stay and increased EBL. Moreover, patients with malnutrition have poor prognosis compared with WO malnutrition group. Preoperative malnutrition was significantly associated with negative long-term OS, DFS, and CSS for patients with Stage IIA/IIB, which is consistent with results of the whole study group. It is still unclear why the preoperative malnutrition has adverse effect on survival. There are several presumptions for this adverse effect on survival. First, the patients with malnutrition may have an immunological disadvantage compared with the WO malnutrition group. There is a strong evidence to suggest that the deficiency of one or more nutrients caused an inadequate immune response of innate and acquired immunity.13,14 Malnutrition can reduce the number of helper T cells, interleukin-2/-3, and T-cell blastogenic response.15 The cumulative consequences of these alterations accelerated tumor progression caused by compromised tumor immunity.16 Secondly, in our study group, the EBL was significantly higher in the malnutrition group. Several reports have demonstrated EBL to be associated with poor outcomes in various types of malignancies.17,18 In a study conducted by Bruns et al,19 EBL greater than 700 mL after gastrointestinal surgery was associated with a significant decrease in natural killer cell activity, producing an unfavorable effect on patient survival. Besides, excessive blood loss during operation can adversely affect the operative field. If the operative field is obscured by blood, obtaining a sufficient resection margin is difficult. Third, malnutrition increases the risk of postoperative complications after surgery.20 It is reported that postoperative complications are also associated with reduced long-term survival.20,21 In the present study, the overall complication rate was significantly higher in the malnutrition group than that in the WO-malnutrition group; however, there was no difference in the major complication rate. Major complication after PD is usually associated with pancreas consistency, pancreatic duct size, and technical failure.22,23 The definition of malnutrition by GLIM may not have a relationship with these factors. However, our previous study showed that malnutrition defined by albumin and BMI is associated with higher major complication rate.24
The association between malnutrition and survival in pancreatic cancer has been reported in a few studies.21 Park et al8 showed that the OS of patients with pancreatic cancer was strongly associated with their baseline nutritional status; however, the study was conducted in inoperable and metastatic pancreatic cancer patients. In a study by Bachmann et al,25 cachexia has a significant impact on survival in patients with pancreatic cancer scheduled for tumor resection. However, they included patients who underwent palliative surgery in their analysis.. Our study analyzed the long-term oncological outcomes dependence on preoperative malnutrition in curative resected pancreatic head cancer patients. Furthermore, we performed the subgroup analysis to evaluate the impact of malnutrition regarding tumor stage.
In this study, we used the GLIM criteria for screening of malnutrition in patients with pancreatic head cancer. It is recommended to assess the nutritional status at the time of diagnosis and throughout treatment, because it will affect the outcome of treatment.20,26,27 There are several methods for screening the malnutrition and the diagnostic criteria for malnutrition may vary among institutions depending on resources. Therefore, there is a need to establish a global and international consensus regarding malnutrition diagnostic methods. The discussion on global malnutrition consensus was initiated in 2016 with participants from 6 continents and 30 countries. They created the GLIM group and have published the criteria of malnutrition for adults. The GLIM criteria are simple and readily applied by clinicians and other health practitioners.9
In our study, the percentage of patients who had lost more than 5% of their usual body weight within past 6 months before the time of admission was 96% for malnutrition group and 44% in the WO-malnutrition group. However, the BMI was similar between the malnutrition and WO-malnutrition groups. GLIM group felt that it is especially important to recognize the unexplained weight loss in the course of disease.9 Possibly, the recent unexplained weight loss in the malnutrition group is more meaningful than the BMI before surgery. Unexplained weight loss in cancer patients is caused by the ongoing loss of skeletal muscle mass with or without fat.28 Several studies have indicated that low muscle mass is associated with poor prognoses in cancer patients.29,30 Low muscle mass may be induced by decreasing protein synthesis and increasing protein degradation, which might decrease the patient’s ability to handle the stress of surgery.31 For these reasons, the malnutrition group appears to have poor prognoses.
A recent Cochrane review identified that preoperative nutritional intervention for a group suffering from malnutrition resulted in a significant reduction in total postoperative complications.32. Moreover, a combination of individualized nutrition counseling, oral nutritional supports, and exercise has been proven to be effective for postoperative outcomes in rehabilitations trials.33–35 According to the European Society for Clinical Nutrition and Metabolism guidelines, nutritional conditioning before surgery must be considered to optimize the mildly malnourished patients’ short-term (7–10 days) outcomes.36 In the case of severely malnourished patient, longer periods are necessary. However, delaying surgery for nutritional support in cancer patients may also negatively affect patient survival. Therefore, it is important to determine the optimal timing and duration of nutritional support before surgery.
Several studies have demonstrated that the introduction of an early oral feeding after PD reduced the length of hospital stay without negatively affecting postoperative morbidity.37 Based on these evidence, we allow our patients to have an early oral feeding after surgery. The patients will be allowed to have 400 mL of carbohydrate-rich drink (Nucare NoNPO, Daesang Welllife, Korea) at postoperative day 1.
This study has limitations. First, the results cannot be generalized because of the risk of bias resulting from the study’s observational and retrospective design. Second, in the present study, we evaluated the patient’s muscle mass through physical examination. Thus, there was no quantifiable data regarding reduced muscle mass. Third, this is a single-center study. Therefore, our findings should be confirmed though further multicenter and prospective studies in large populations.
Despite these limitations, there are several clinically significant messages of our study. First, preoperative nutritional status is associated with poor prognosis in patients with pancreatic head cancer. Second, to improve the outcomes in these patients, it may be necessary to enhance their preoperative nutritional status. Therefore, the patients with malnutrition before surgery should be monitored and treated with adequate nutritional support.
Footnotes
Disclosure: The authors declare that they have nothing to disclose.
B.L. and H.S.H. participated in research design, writing of the article, and performance of the research and participated in data analysis. Y.S.Y. participated in research design and data analysis.
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