Skip to main content
Download PDF

Effect of body fat mass loss on prognosis of radical resection for pancreatic ductal adenocarcinoma based on bioelectrical impedance analysis

BMC Surgery volume 24, Article number: 19 (2024) Cite this article

Abstract

Background

Few reports have performed a prognostic analysis based on bioelectrical impedance analysis in patients with radical resection of pancreatic ductal adenocarcinoma (PDAC), and its usefulness in prognostic analysis remains unclear. This study aimed to evaluate body composition changes in patients undergoing radical resection for PDAC and analyze its impact on prognosis.

Methods

The medical records of radical resection for patients with PDAC were retrospectively reviewed, and the parameters of body composition, including body weight, skeletal muscle mass, body fat mass (BFM), and extracellular water-total body water ratio, from preoperatively to 12 months postoperatively, for each surgical procedure were measured based on direct segmental multifrequency bioelectrical impedance analysis with an InBody 770 (InBody Inc., Tokyo, Japan) device. The clinicopathological and prognostic factors were analyzed.

Results

Among 79 patients who underwent radical resection for PDAC, 36 (46%), 7 (8%), and 36 (46%) underwent pancreatoduodenectomy, total pancreatectomy, and distal pancreatectomy, respectively. The multivariate overall survival analysis demonstrated that BFM loss percentage at 1 month postoperatively ≧14% (p = 0.021), lymph node metastasis (p = 0.014), and non-adjuvant chemotherapy (p <  0.001) were independent poor prognostic factors. Multivariate analysis revealed that preoperative BFM < 12 kg and preoperative albumin < 3.5 g/dL were independently associated with BFM loss percentage at 1 month postoperatively ≧14% (p = 0.021 and p = 0.047, respectively).

Conclusions

Loss of BFM in the early postoperative period may have a poor prognosis in radical resection of PDAC.

Peer Review reports

Background

Surgical resection is the only curative treatment option for pancreatic ductal adenocarcinoma (PDAC). Additionally, multidisciplinary treatment, including neoadjuvant and adjuvant therapies, has become the standard for PDAC in recent years [1]. However, even if curative resection is performed, the 5-year overall survival (OS) rate remains low at 20.7–44.1% [1,2,3]. Previous reports have investigated the impact of preoperative nutritional evaluation and body composition evaluation on the long-term prognosis of PDAC. Non-invasive nutritional status assessment includes nutritional risk screening such as nutritional risk screening 2002 (NRS2002) [4]. It also includes the assessment of anthropometric parameters such as body weight (BW) and height to calculate body mass index (BMI) and body composition parameters comprising skeletal muscle mass (SMM), skeletal muscle mass index (SMI), and body fat mass (BFM). Presence of inflammation reduces serum albumin concentrations, regardless of the underlying nutritional status. Therefore, blood biochemical findings such as the Glasgow Prognostic Score (GPS), modified Glasgow Prognostic Score (mGPS) [5, 6], and Prognostic Nutritional Index (PNI) [7, 8] are recognized to be associated with nutrition risk rather than malnutrition itself. The evaluation of the psoas major [9, 10] and general skeletal muscles [11] using abdominal computed tomography (CT) images have reported that patients with a poor preoperative nutritional status and sarcopenia may have poor long-term prognosis. In addition, poor preoperative nutritional status, sarcopenia, and visceral obesity may be associated with postoperative complications [12, 13].

Bioelectrical impedance analysis (BIA) is a non-invasive method widely used for evaluating body composition parameters, including SMM, SMI, BFM, extracellular water-total body water ratio (ECW/TBW), and phase angle (PhA). However, there is a scarcity of reports showing the effect of early postoperative body composition changes assessed by BIA on the long-term prognosis of radical resection for PDAC. Therefore, this study aimed to evaluate the body composition changes in the early postoperative period following radical resection for PDAC and analyze their impact on prognosis.

Methods

Study design

We retrospectively reviewed the medical records of patients who underwent radical resection for PDAC at the Department of Surgery of the National Hospital Organization Kure Medical Center in Hiroshima, Japan, between August 2016 and July 2022. This Institutional Review Board of National Hospital Organization Kure Medical Center (2023–17) approved this study, which was conducted following the principles of the Declaration of Helsinki. In addition, all patients provided written informed consent.

Neoadjuvant therapy

In our institution, neoadjuvant therapy (NAT) has been administered to patients with resectable PDAC since 2019, as well as to those with borderline resectable (BR) or locally advanced (LA) PDAC with arterial contacts, such as the superior mesenteric, hepatic, or celiac arteries, since 2016. Previously, all patients with resectable pancreatic cancer had received surgery upfront. NAT regimens for patients with resectable PDAC included gemcitabine/S-1, while those for patients with BR/LA PDAC included gemcitabine/nab-paclitaxel/S-1, gemcitabine/nab-paclitaxel, and 5-fluorouracil/leucovorin/irinotecan/oxaliplatin. No patient received radiation therapy during the study period.

Perioperative nutritional support

We administered oral supplementation containing arginine, ω-3 fatty acids, and RNA (oral IMPACT®; Nestle Japan Co., Ltd., Tokyo, Japan) to all patients with PDAC for 5 days before surgery [14,15,16]. Moreover, we performed pancreatic enzyme replacement therapy (PERT) before and after surgery. Regarding this therapy, the patients received the pancreatic digestive enzyme supplement LipaCreon® (150 mg, 12 times/day; VIATRIS, Tokyo, Japan), particularly those with decreased serum lipase, decreased serum pancreatic amylase, or main pancreatic duct obstruction before surgery from 2021, and after surgery from 2016 in our department [17,18,19].

Data collection

Patient demographic and clinicopathological data for each surgical procedure included age, sex, initial carbohydrate antigen 19–9 (CA19–9) level, preoperative PNI, GPS, NRS2002 [4], and resectability status according to the National Comprehensive Cancer Network guideline version 22,021 [20], operating time, operative blood loss, pathological tumor size, lymph node metastasis, and adjuvant chemotherapy. Postoperative complications were defined as those with a Clavien–Dindo classification ≧Grade III [21]. The body composition parameters included the SMM, SMI, BFM, ECW/TBW, and whole body PhA, and were measured preoperatively and at 1, 6, and 12 months postoperatively based on direct segmental multifrequency BIA with an InBody 770 device (InBody Inc., Tokyo, Japan). We measured body composition using InBody at more than 2 hours after breakfast without intentional physical activity at the morning of the examination. Each patient had their usual breakfast without restrictions on breakfast. The patients stood barefoot on the scale and aligned their heels with round electrodes. Thereafter, they held the hand electrode and placed their thumb on the round electrode. With the arm straight and not contacting with the body, the impedance of five body parts (i.e., right arm, left arm, trunk, right leg, and left leg) was measured at six different frequencies (1 kHz, 5 kHz, 50 kHz, 250 kHz, 500 kHz, and 1000 kHz), while the reactance of the five body parts at three frequencies (5 kHz, 50 kHz, and 250 kHz) was also measured. The BIA has been assessed in normal populations, athletes, elderly, and hemodialysis patients, and closely correlates with the gold standard measurement by dual energy X-ray absorptiometry, underwater weight method, and air displacement plethysmography [22,23,24,25,26]. This tool is not based on statistical data of any specific population. Therefore, it is capable of accurately assessing patients with very different physical types, whether obese, elderly or athletic [27, 28].

Adjuvant therapy and surveillance

Adjuvant chemotherapy was recommended to all patients and was administered to those who were tolerant and consenting after radical pancreatectomy. Regular surveillance was performed via blood testing, which included tumor markers and multidetector CT at intervals of 3–6 months. When two or more modalities, such as magnetic resonance imaging or positron emission tomography-CT, indicated a recurrence or recurrent lesion at two different time points, recurrence was confirmed and recorded. The survival time after surgery and cause of death were also recorded for the patients who died, and the OS time and recurrence status were recorded for those who survived.

Statistical analysis

Data are expressed as medians and ranges or as absolute values and percentages. The chi-square or Fisher’s exact test was used for the categorical variables, while the Wilcoxon two-sample test was used to compare continuous variables in the univariate analysis. A paired t-test with Bonferroni correction was used for body composition changes. Survival curves were obtained using the Kaplan–Meier method, and the log-rank test was used to compare distributions. The proportional hazard regression model (Cox regression) was used to perform multivariate survival analyses. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated, and cutoff values were defined by receiver operating characteristic (ROC) curve analysis for 3-year OS after surgery. Preoperative low SMI was defined as SMI < 7.0 kg/m2 in male and SMI < 5.7 kg/m2 in female patients [29]. The cutoff PNI value was set at 45 as previously described [30]. All tests were two-sided, with statistical significance set at p <  0.05. All statistical analyses were performed using JMP statistical software (version 16.0; SAS Institute, Cary, NC, USA).

Results

Patients

A total of 79 patients underwent radical resection for PDAC. The clinicopathological characteristics of the patients for each surgical procedure are presented in Table 1. Among 79 patients who underwent radical resection for PDAC, 36 (46%), 7 (8%), and 36 (46%) underwent pancreatoduodenectomy (PD), total pancreatectomy (TP), and distal pancreatectomy (DP), respectively. Preoperative BMI and preoperative serum albumin levels were significantly lower in the PD group among the three groups (21.2, 21.5, 23.1 kg/m2, respectively; p = 0.033; and 3.6, 3.9, and 3.8 g/mL, respectively; p = 0.045). The number of patients with preoperative NRS2002 ≧3 was significantly higher in the PD group compared to the other groups (p = 0.005). Operating time and operative blood loss were significantly higher in the TP group among the three groups (499, 515, and 373 min, respectively; p <  0.001; and 460, 640, and 200 mL, respectively; p <  0.001). The number of patients who underwent postoperative PERT was significantly lower in the DP group compared to the other groups (p <  0.001).

Table 1 Patients’ characteristics (n = 79)
Full size table

Body composition changes

The analysis of postoperative mean body composition showed that the mean SMMs in the PD group preoperatively and at 1, 6, and 12 months postoperatively were 21.3 ± 4.9, 21.1 ± 5.1, 21.3 ± 5.5, and 21.4 ± 5.5 kg, respectively; the corresponding values in the TP group were 21.5 ± 3.2, 21.3 ± 4.5, 21.7 ± 4.9, and 21.3 ± 4.5 kg, respectively; and, in the DP group, these values were 22.3 ± 4.4, 21.9 ± 5.0, 22.3 ± 4.7, and 22.4 ± 4.9 kg, respectively (Fig. 1a). No significant difference was observed for any period. The mean BFM in the PD group was 13.7 ± 6.4, 11.7 ± 6.6, 9.5 ± 4.7 kg, and 9.6 ± 4.1 kg; the corresponding values in the TP group were 13.5 ± 3.2, 10.7 ± 7.9, 7.3 ± 2.4, and 7.9 ± 2.7 kg; and, in the DP group, these values were 16.3 ± 6.3, 14.5 ± 6.4, 12.7 ± 5.9, and 13.2 ± 5.5 kg, respectively (Fig. 1b). The BFM in the PD and DP groups at 1, 6, and 12 months postoperatively significantly decreased compared to the preoperative BFM. The mean ECW/TBW in the PD group was 0.397 ± 0.009, 0.403 ± 0.010, 0.404 ± 0.012, and 0.401 ± 0.010; the corresponding values in the TP group were 0.400 ± 0.010, 0.407 ± 0.011, 0.408 ± 0.002, and 0.405 ± 0.005, respectively; and, in the DP group, these values were 0.400 ± 0.008, 0.401 ± 0.012, 0.401 ± 0.009, and 0.400 ± 0.010, respectively (Fig. 1c). The ECW/TBW in the PD group at 1, 6, and 12 months postoperatively and the corresponding values in the TP group at 6 months postoperatively significantly increased compared to the preoperative ECW/TBW. The mean PhA in the PD group preoperatively and at 1, 6, and 12 months postoperatively was 4.2 ± 0.7 and 3.8 ± 0.6, 3.9 ± 0.7, and 4.1 ± 0.8, respectively. The corresponding values in the TP group were 4.3 ± 0.7 and 3.8 ± 0.6, 3.8 ± 0.6, and 3.7 ± 0.3, respectively. Furthermore, in the DP group, these values were 4.1 ± 0.6 and 4.1 ± 0.6, 4.0 ± 0.8, and 4.0 ± 0.7, respectively (Fig. 1d). The PhA in the PD group at 1, 6, and 12 months postoperatively and the corresponding values in the TP group at 1 months postoperatively significantly decreased compared to the preoperative PhA value. The impedance and reactance of the five body parts are presented in Additional file 1.

Fig. 1
figure 1

Mean body composition preoperatively and at 1, 6, and 12 months postoperatively for each surgical procedure (a) SMM, (b) BFM, (c) ECW/TBW, and (d) PhA. BFM, body fat mass; DP, distal pancreatectomy; ECW/TBW, extracellular water-total body water ratio; NS, not significant; PD, pancreatoduodenectomy; SMM, skeletal muscle mass; TP, total pancreatectomy; PhA, phase angle *, p < 0.05

Full size image

Survival analysis

The median follow-up period was 25.4 (range, 2.9–73.5) months, and the survival curve of all patients showed that the median survival time (MST) after surgery was 44.6 months (Fig. 2a). The postoperative 1-, 3- and 5-year survival rates were 89, 61, and 42%, respectively. The median relapse-free survival (RFS) after surgery was 24.1 months (Fig. 2b), and the postoperative 1-, 3- and 5-year RFS rates were 71, 44, and 40%, respectively. The univariate and multivariate OS analyses of the factors predictive of a poor prognosis are shown in Table 2. Univariate OS analysis of poor prognostic factors demonstrated that BFM loss percentage at 1 month postoperatively ≧14% (p = 0.021), lymph node metastasis (p = 0.030), and no-adjuvant chemotherapy (p <  0.001) were significantly associated with OS. Furthermore, multivariate analysis demonstrated that BFM loss percentage 1 month after surgery ≧14% (HR, 2.52; 95% CI, 1.15–5.55; p = 0.021), lymph node metastasis (HR, 3.61; 95% CI, 1.30–10.02; p = 0.014), and no-adjuvant chemotherapy (HR, 13.30; 95% CI, 4.08–43.41; p < 0.001) were independent poor prognostic factors. The survival curves of patients stratified by BFM loss percentage at 1 month postoperatively ≧14%, divided into the BFM loss group (BLG) or the normal group (NG), are shown in Fig. 3. The median OS rate after surgery was significantly worse in the BLG than in the NG (38.8 vs 64.0 months, p = 0.021) (Fig. 3a). The RFS postoperatively was stratified by the BLG or NG. There was no significant difference in the median RFS after surgery between the two groups (19.6 vs 43.3 months, p = 0.464) (Fig. 3b). The 86% of patients in the BLG and 88% of those in the NG underwent adjuvant chemotherapy (p = 0.830). The 51% of patients in the BLG and 45% of those in the NG recurred (p = 0.587). The multivariate analysis revealed that preoperative BFM < 12 kg and preoperative albumin < 3.5 g/dL were independently associated with BFM loss percentage at 1 month postoperatively ≧14% (odds ratio [OR], 4.03; 95% CI, 1.23–13.19; p = 0.021 and OR, 3.13; 95% CI, 1.02–9.63; p = 0.047, respectively) (Table 3).

Fig. 2
figure 2

The survival curve for all patients (a) Overall survival after surgery (b) Relapse free survival after surgery

Full size image
Table 2 Univariate and multivariate overall survival analyses of poor prognostic factors (n = 79)
Full size table
Fig. 3
figure 3

Survival curves stratified by BFM loss percentage ≧14% at 1 month postoperatively (a) The median overall survival rate after surgery was significantly worse in the BLG than in the NG (p = 0.021). (b) The relapse free survival after surgery stratified by the BLG or NG. There was no significant difference in median relapse free survival after surgery between the two groups (p = 0.464). BLG, body fat mass loss group; NG, normal group

Full size image
Table 3 Multivariate analyses of factors associated with BFM loss percentage 1 month after surgery ≧ 14%
Full size table

Discussion

This study revealed that BFM loss in the early postoperative period in patients having undergone radical resection for PDAC may lead to poor prognosis based on direct segmental multifrequency BIA assessment. Currently, there are no established methods for evaluating the nutritional status and body composition in patients with PDAC; however, there have been various reports about the impact on long-term prognosis after surgery for PDAC based on blood biochemistry findings or body composition changes. Previously, Kim et al. reported that a low PNI change (− 1.94) between pre- and post-neoadjuvant chemotherapy (NAC) was an independent risk factor for the OS of patients with resected PDAC following NAC. In the preoperative setting, improving the PNI can improve the long-term oncologic outcomes of PDAC [7]. Abe et al. [30] found that preoperative PNI ≧45 in patients undergoing surgical resection for PDAC may be associated with good prognosis. In addition, Yamada, et al. indicated that a GPS score of 2 points was a significant independent poor prognostic factor in patients that underwent pancreatic cancer resection [31]. Regarding body composition changes, many studies have used abdominal CT imaging. In previous reports, preoperative visceral adiposity and sarcopenic visceral obesity, as well as low muscle mass and quality, were found to be associated with mortality and recurrence after resection of PDAC [11], and postoperative skeletal muscle changes were independently associated with prognostic factors [32].

BIA is widely used as it is a simple and non-invasive method that provides accurate results [33, 34]. Several reports have evaluated postoperative changes in body composition using BIA and analyzed the risk factors for postoperative complications in patients with gastric cancer [35,36,37]. Moreover, in patients with colorectal cancer, a preoperative low SMI based on the BIA method was considered a risk factor for postoperative ileus [38], and preoperative visceral fat area measured by BIA was an independent prognostic factor for disease-free survival [39]. Only a few studies have investigated the relationship between the prognosis after radical resection of PDAC and body composition changes assessed by BIA. Gupta et al. reported that the phase angle used as an index for evaluating cell membranes and intra- and extracellular water balance was a strong prognostic indicator in advanced PDAC, and patients with a phase angle > 5.0° had a significantly better prognosis than those with a phase angle < 5.0° (MST, 10.2 vs 6.3 months, p = 0.02) [40]. Additionally, Tozuka, et al. revealed that SMI obtained by BIA may be a predictor of treatment response and prognosis in patients with advanced PDAC who underwent gemcitabine plus nab-paclitaxel combination therapy, and the progression-free survival in the sarcopenia group was significantly lower compared with that of the non-sarcopenia group (4.4 vs 6.4 months, p = 0.03) [41]. In the current study, the SMM did not change significantly, while the BFM changed significantly from preoperatively to 12 months postoperatively; therefore, we speculated that the rate of BFM change may be a sensitive reflection of malnutrition related to prognosis. Among the 79 patients who underwent radical resection for PDAC, 53 patients (67%) (31, 7, and 15 patients in the PD, TP, and DP groups, respectively) underwent postoperative PERT. Moreover, in our department, from the day after surgery, the patients could walk around the ward with a physical therapist as postoperative physical exercise. This may have led to the maintenance of SMM. Although there was no statistically significant difference, serum C-reactive protein 1 month after surgery measuring ≧1 mg/dl tended to be involved in BFM loss percentage 1 month after surgery ≧ 14%. Prolonged inflammation after surgery may have contributed to BFM loss. Recent reports have stated that marked loss of muscle, visceral fat, or subcutaneous fat significantly predicted shorter disease-free survival (DFS) and OS among patients with gastric cancer who underwent gastrectomy [42], and the marked loss of adipose tissue was found to be associated with a poor nutritional status. Poorer OS and DFS rates were observed in patients with marked visceral adipose tissue loss and subcutaneous adipose tissue loss during neoadjuvant treatment [43]. However, to our knowledge, no report to date has shown the relationship between postoperative BFM loss and prognosis of radical resection for PDAC. Therefore, BFM loss in the early postoperative period may reflect poor general condition.

Among gastrointestinal cancer procedures, pancreatectomy for PDAC is a highly invasive surgery. Body composition changes result from various mechanisms, such as hyper-catabolism associated with the inflammatory reactions caused by surgical stress, reduced food intake, and a decline in activity. In cases of surgical stress, immune cells produce cytokines that act as mediators of both immune and systemic responses to injury. Muscle catabolism is accelerated by the cytokines produced during and after surgery, leading to a decrease in muscle content after surgery [44]. Cytokines associated with inflammatory reactions could possibly cause the adverse feedback action of leptin on the hypothalamus, causing a loss of appetite [45]. Furthermore, patients who underwent PDAC lose the largest percentage of BW until discharge from the department compared to those with gastric cancer and colorectal cancer [46]; however, according to another previous report considering operative methods, BW change 12 months after surgery in the PD group was significantly lower than that found in the total gastrectomy and distal gastrectomy groups [47]. Therefore, there may be differences in the way body composition changes based on the postoperative period (until discharge from the department or 12 months after surgery) and operation methods such as PD, total gastrectomy, or distal gastrectomy. In our study, patients who underwent TP tended to lose more weight postoperatively than those who underwent PD or DP, without a significant difference, because of the small number of patients. This probably reflects the fact that most of the cases in the TP group included patients with highly malignant tumors with combined resection of the portal vein, and the surgical invasion was larger than that in corresponding patients who underwent PD or DP. There is no established method to reduce postoperative BW and BFM loss; in fact, our study showed that preoperative BFM < 12 kg and preoperative albumin < 3.5 g/dL were independently associated with BFM loss percentage at 1 month postoperatively ≧14%. However, no association with postoperative complications was found. This suggests the importance of preoperative factors and maintaining performance status and exercise tolerance. The maintenance of body composition changes in SMM and BFM through nutritional support comprised preoperative immunonutrition [16], PERT [17, 18], exercise therapy, and rehabilitation before and after surgery, which may lead to reducing postoperative complications and improving prognosis. Ausania et al. reported that prehabilitation that includes preoperative exercise therapy for patients with pancreatic or periampullary tumors who were candidates for pancreaticoduodenectomy was significantly associated with lower delayed gastric emptying incidence [48]. Additionally, Bundred et al. [49] indicated that prehabilitation programs may improve postoperative outcomes following pancreatic surgery. Current prehabilitaton programs for patients undergoing pancreatic resection include diverse exercise regimens, and there is no consensus regarding timing or length of prehabilitation; thus, there is a need to establish standardized prehabilitation programs in pancreatic surgery. Moreover, the importance of enhanced recovery after surgery protocols [50] for patients with PDAC has been emphasized.

This study had some limitations. First, it only included patients from a single institution, and the number of patients who underwent radical resection for PDAC was small. Hence, further studies using multicenter data or a nationwide database with a larger number of patients are needed. Second, this study had a retrospective design based on data not primarily meant for research. Third, we determined cutoff values based on the ROC curves for 3-year OS after surgery; however, no specific cutoff values for the PDAC population exist and, therefore, further investigations are necessary.

Conclusion

BFM loss in the early postoperative period in patients having undergone radical resection for PDAC may lead to poor prognosis based on direct segmental multifrequency BIA assessment.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

BFM:

Body fat mass

BIA:

Bioelectrical impedance analysis

BLG:

Body fat mass loss group

BMI:

Body mass index

BR:

Borderline resectable

BW:

Body weight

CA19–9:

Carbohydrate antigen 19–9

CI:

Confidence intervals

CT:

Computed tomography

DP:

Distal pancreatectomy

ECW/TBW:

Extracellular water-total body water ratio

GPS:

Glasgow Prognostic Score

HR:

Hazard ratios

LA:

Locally advanced

mGPS:

modified Glasgow prognostic score

MST:

Median survival time

NAC:

Neoadjuvant chemotherapy

NAT:

Neoadjuvant therapy

NRS2002:

Nutritional risk screening 2002

NG:

Normal group

OS:

Overall survival

PD:

Pancreatoduodenectomy

PDAC:

Pancreatic ductal adenocarcinoma

PERT:

Pancreatic enzyme replacement therapy

PhA:

Phase angle

PNI:

Prognostic nutritional index

RFS:

Relapse-free survival

ROC:

Receiver operating characteristic

SMI:

Skeletal muscle mass index

SMM:

Skeletal muscle mass

TP:

Total pancreatectomy

References

  1. Uesaka K, Boku N, Fukutomi A, Okamura Y, Konishi M, Matsumoto I, Kaneoka Y, Shimizu Y, Nakamori S, Sakamoto H, et al. Adjuvant chemotherapy of S-1 versus gemcitabine for resected pancreatic cancer: a phase 3, open-label, randomised, non-inferiority trial (JASPAC 01). Lancet. 2016;388(10041):248–57.

    Article  CAS  PubMed  Google Scholar 

  2. Oettle H, Neuhaus P, Hochhaus A, Hartmann JT, Gellert K, Ridwelski K, Niedergethmann M, Zülke C, Fahlke J, Arning MB, et al. Adjuvant chemotherapy with gemcitabine and long-term outcomes among patients with resected pancreatic cancer: the CONKO-001 randomized trial. Jama. 2013;310(14):1473–81.

    Article  CAS  PubMed  Google Scholar 

  3. Neoptolemos JP, Palmer DH, Ghaneh P, Psarelli EE, Valle JW, Halloran CM, Faluyi O, O’Reilly DA, Cunningham D, Wadsley J, et al. Comparison of adjuvant gemcitabine and capecitabine with gemcitabine monotherapy in patients with resected pancreatic cancer (ESPAC-4): a multicentre, open-label, randomised, phase 3 trial. Lancet. 2017;389(10073):1011–24.

    Article  CAS  PubMed  Google Scholar 

  4. Kondrup J, Rasmussen HH, Hamberg O, Stanga Z. Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials. Clin Nutr. 2003;22(3):321–36.

    Article  PubMed  Google Scholar 

  5. Onoe S, Yokoyama Y, Kokuryo T, Igami T, Mizuno T, Yamaguchi J, Watanabe N, Kawakatsu S, Ebata T. A presurgical prognostic stratification based on nutritional assessment and carbohydrate antigen 19-9 in pancreatic carcinoma: an approach with nonanatomic biomarkers. Surgery. 2021;169(6):1463–70.

    Article  PubMed  Google Scholar 

  6. Hoshimoto S, Hishinuma S, Shirakawa H, Tomikawa M, Ozawa I, Ogata Y. Validation and clinical usefulness of pre- and postoperative systemic inflammatory parameters as prognostic markers in patients with potentially resectable pancreatic cancer. Pancreatology. 2020;20(2):239–46.

    Article  PubMed  Google Scholar 

  7. Kim KH, Hwang HK, Kang IC, Lee WJ, Kang CM. Oncologic impact of preoperative prognostic nutritional index change in resected pancreatic cancer following neoadjuvant chemotherapy. Pancreatology. 2020;20(2):247–53.

    Article  PubMed  Google Scholar 

  8. Kawai M, Hirono S, Okada KI, Miyazawa M, Shimizu A, Kitahata Y, Kobayashi R, Ueno M, Hayami S, Tanioka K, et al. Low lymphocyte monocyte ratio after neoadjuvant therapy predicts poor survival after pancreatectomy in patients with borderline resectable pancreatic cancer. Surgery. 2019;165(6):1151–60.

    Article  PubMed  Google Scholar 

  9. Delitto D, Judge SM, George TJ Jr, Sarosi GA, Thomas RM, Behrns KE, Hughes SJ, Judge AR, Trevino JG. A clinically applicable muscular index predicts long-term survival in resectable pancreatic cancer. Surgery. 2017;161(4):930–8.

    Article  PubMed  Google Scholar 

  10. Okumura S, Kaido T, Hamaguchi Y, Fujimoto Y, Masui T, Mizumoto M, Hammad A, Mori A, Takaori K, Uemoto S. Impact of preoperative quality as well as quantity of skeletal muscle on survival after resection of pancreatic cancer. Surgery. 2015;157(6):1088–98.

    Article  PubMed  Google Scholar 

  11. Okumura S, Kaido T, Hamaguchi Y, Kobayashi A, Shirai H, Yao S, Yagi S, Kamo N, Hatano E, Okajima H, et al. Visceral adiposity and Sarcopenic visceral obesity are associated with poor prognosis after resection of pancreatic Cancer. Ann Surg Oncol. 2017;24(12):3732–40.

    Article  PubMed  Google Scholar 

  12. Kanda M, Fujii T, Kodera Y, Nagai S, Takeda S, Nakao A. Nutritional predictors of postoperative outcome in pancreatic cancer. Br J Surg. 2011;98(2):268–74.

    Article  CAS  PubMed  Google Scholar 

  13. Pecorelli N, Carrara G, De Cobelli F, Cristel G, Damascelli A, Balzano G, Beretta L, Braga M. Effect of sarcopenia and visceral obesity on mortality and pancreatic fistula following pancreatic cancer surgery. Br J Surg. 2016;103(4):434–42.

    Article  CAS  PubMed  Google Scholar 

  14. Beale RJ, Bryg DJ, Bihari DJ. Immunonutrition in the critically ill: a systematic review of clinical outcome. Crit Care Med. 1999;27(12):2799–805.

    Article  CAS  PubMed  Google Scholar 

  15. Heyland DK, Novak F, Drover JW, Jain M, Su X, Suchner U. Should immunonutrition become routine in critically ill patients? A systematic review of the evidence. Jama. 2001;286(8):944–53.

    Article  CAS  PubMed  Google Scholar 

  16. Aida T, Furukawa K, Suzuki D, Shimizu H, Yoshidome H, Ohtsuka M, Kato A, Yoshitomi H, Miyazaki M. Preoperative immunonutrition decreases postoperative complications by modulating prostaglandin E2 production and T-cell differentiation in patients undergoing pancreatoduodenectomy. Surgery. 2014;155(1):124–33.

    Article  PubMed  Google Scholar 

  17. Pezzilli R, Caccialanza R, Capurso G, Brunetti O, Milella M, Falconi M. Pancreatic enzyme replacement therapy in pancreatic Cancer. Cancers (Basel). 2020;12(2).

  18. Roeyen G, Berrevoet F, Borbath I, Geboes K, Peeters M, Topal B, Van Cutsem E, Van Laethem JL. Expert opinion on management of pancreatic exocrine insufficiency in pancreatic cancer. ESMO Open. 2022;7(1):100386.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Nakamura H, Murakami Y, Uemura K, Hayashidani Y, Sudo T, Ohge H, Sueda T. Predictive factors for exocrine pancreatic insufficiency after pancreatoduodenectomy with pancreaticogastrostomy. J Gastrointest Surg. 2009;13(7):1321–7.

    Article  PubMed  Google Scholar 

  20. Tempero MA, Malafa MP, Al-Hawary M, Behrman SW, Benson AB, Cardin DB, Chiorean EG, Chung V, Czito B, Del Chiaro M, et al. Pancreatic adenocarcinoma, version 2.2021, NCCN clinical practice guidelines in oncology. J Natl Compr Cancer Netw. 2021;19(4):439–57.

    Article  CAS  Google Scholar 

  21. Dindo D, Demartines N, Clavien PA. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205–13.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Kim M, Shinkai S, Murayama H, Mori S. Comparison of segmental multifrequency bioelectrical impedance analysis with dual-energy X-ray absorptiometry for the assessment of body composition in a community-dwelling older population. Geriatr Gerontol Int. 2015;15(8):1013–22.

    Article  PubMed  Google Scholar 

  23. Utter AC, Lambeth PG. Evaluation of multifrequency bioelectrical impedance analysis in assessing body composition of wrestlers. Med Sci Sports Exerc. 2010;42(2):361–7.

    Article  PubMed  Google Scholar 

  24. Fürstenberg A, Davenport A. Comparison of multifrequency bioelectrical impedance analysis and dual-energy X-ray absorptiometry assessments in outpatient hemodialysis patients. Am J Kidney Dis. 2011;57(1):123–9.

    Article  PubMed  Google Scholar 

  25. So W-Y, Swearingin B, Crooms B, Lee R, Choi Y, Dail T, Melton D, Fuller T, Ha C. Body composition measurements determined by air displacement plethysmography and eight-polar bioelectrical impedance analysis are equivalent in African American college students. HealthMED. 2012;6:1896–9.

    Google Scholar 

  26. Foster KR, Lukaski HC. Whole-body impedance--what does it measure? Am J Clin Nutr. 1996;64(3 Suppl):388s–96s.

    Article  CAS  PubMed  Google Scholar 

  27. Cha K, Chertow GM, Gonzalez J, Lazarus JM, Wilmore DW. Multifrequency bioelectrical impedance estimates the distribution of body water. J Appl Physiol (1985). 1995;79(4):1316–9.

    Article  CAS  PubMed  Google Scholar 

  28. Cha K, Shin S, Shon C, Choi S, Wilmore D. Evaluation of segmental bioelectrical impedance analysis for measuring muscle distribution. J Ichper SD-Asia. 1997;1:11–6.

    Google Scholar 

  29. Chen LK, Woo J, Assantachai P, Auyeung TW, Chou MY, Iijima K, Jang HC, Kang L, Kim M, Kim S, et al. Asian working Group for Sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020;21(3):300-307.e302.

    Article  PubMed  Google Scholar 

  30. Abe T, Nakata K, Kibe S, Mori Y, Miyasaka Y, Ohuchida K, Ohtsuka T, Oda Y, Nakamura M. Prognostic value of preoperative nutritional and immunological factors in patients with pancreatic ductal adenocarcinoma. Ann Surg Oncol. 2018;25(13):3996–4003.

    Article  PubMed  Google Scholar 

  31. Yamada S, Fujii T, Yabusaki N, Murotani K, Iwata N, Kanda M, Tanaka C, Nakayama G, Sugimoto H, Koike M, et al. Clinical implication of inflammation-based prognostic score in pancreatic Cancer: Glasgow prognostic score is the Most reliable parameter. Medicine (Baltimore). 2016;95(18):e3582.

    Article  CAS  PubMed  Google Scholar 

  32. Choi MH, Yoon SB, Lee K, Song M, Lee IS, Lee MA, Hong TH, Choi MG. Preoperative sarcopenia and post-operative accelerated muscle loss negatively impact survival after resection of pancreatic cancer. J Cachexia Sarcopenia Muscle. 2018;9(2):326–34.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Jaffrin MY, Morel H. Body fluid volumes measurements by impedance: a review of bioimpedance spectroscopy (BIS) and bioimpedance analysis (BIA) methods. Med Eng Phys. 2008;30(10):1257–69.

    Article  PubMed  Google Scholar 

  34. Kitamura A, Seino S, Abe T, Nofuji Y, Yokoyama Y, Amano H, Nishi M, Taniguchi Y, Narita M, Fujiwara Y, et al. Sarcopenia: prevalence, associated factors, and the risk of mortality and disability in Japanese older adults. J Cachexia Sarcopenia Muscle. 2021;12(1):30–8.

    Article  PubMed  Google Scholar 

  35. Kiyama T, Mizutani T, Okuda T, Fujita I, Tokunaga A, Tajiri T, Barbul A. Postoperative changes in body composition after gastrectomy. J Gastrointest Surg. 2005;9(3):313–9.

    Article  PubMed  Google Scholar 

  36. Osaki T, Matsunaga T, Makinoya M, Shishido Y, Miyatani K, Uchinaka E, Tada Y, Ashida K, Tatebe S, Fujiwara Y. Impact of gastrectomy on body composition within 1 month in patients with gastric cancer. Surg Today. 2023;53(7):834–44.

    Article  CAS  PubMed  Google Scholar 

  37. Shiomi S, Toriumi T, Yagi K, Asaoka R, Okumura Y, Wakamatsu K, Aikou S, Yamashita H, Nomura S, Seto Y. Trunk fat volume can be a predictor of postoperative complications after gastrectomy: a retrospective cohort study. BMC Surg. 2021;21(1):207.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Sasaki M, Fukuoka T, Shibutani M, Sugimoto A, Maeda K, Ohira M. Usefulness of the skeletal muscle index in postoperative ileus of colorectal cancer patients: a retrospective cohort study. BMC Surg. 2022;22(1):448.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Kim KE, Bae SU, Jeong WK, Baek SK. Impact of preoperative visceral fat area measured by bioelectrical impedance analysis on clinical and oncologic outcomes of colorectal Cancer. Nutrients. 2022;14(19).

  40. Gupta D, Lis CG, Dahlk SL, Vashi PG, Grutsch JF, Lammersfeld CA. Bioelectrical impedance phase angle as a prognostic indicator in advanced pancreatic cancer. Br J Nutr. 2004;92(6):957–62.

    Article  CAS  PubMed  Google Scholar 

  41. Tozuka Y, Ueno M, Kobayashi S, Morimoto M, Fukushima T, Sano Y, Kawano K, Hanaoka A, Tezuka S, Asama H, et al. Prognostic significance of sarcopenia as determined by bioelectrical impedance analysis in patients with advanced pancreatic cancer receiving gemcitabine plus nab-paclitaxel: a retrospective study. Oncol Lett. 2022;24(4):375.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Park HS, Kim HS, Beom SH, Rha SY, Chung HC, Kim JH, Chun YJ, Lee SW, Choe EA, Heo SJ, et al. Marked loss of muscle, visceral fat, or subcutaneous fat after gastrectomy predicts poor survival in advanced gastric Cancer: single-center study from the CLASSIC trial. Ann Surg Oncol. 2018;25(11):3222–30.

    Article  PubMed  Google Scholar 

  43. Zhang Y, Li Z, Jiang L, Xue Z, Ma Z, Kang W, Ye X, Liu Y, Jin Z, Yu J. Marked loss of adipose tissue during neoadjuvant therapy as a predictor for poor prognosis in patients with gastric cancer: a retrospective cohort study. J Hum Nutr Diet. 2021;34(3):585–94.

    Article  PubMed  Google Scholar 

  44. Aoyama T, Maezawa Y, Yoshikawa T, Segami K, Kano K, Hayashi T, Yamada T, Numata M, Goda M, Tamagawa H, et al. Comparison of weight and body composition after gastrectomy between elderly and non-elderly patients with gastric Cancer. In Vivo. 2019;33(1):221–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Poulia KA, Sarantis P, Antoniadou D, Koustas E, Papadimitropoulou A, Papavassiliou AG, Karamouzis MV. Pancreatic Cancer and Cachexia-metabolic mechanisms and novel insights. Nutrients. 2020;12(6).

  46. Dzierzek P, Kurnol K, Hap W, Frejlich E, Diakun A, Karwowski A, Kotulski K, Rudno-Rudzinska J, Kielan W. Assessment of changes in body composition measured with bioelectrical impedance in patients operated for pancreatic, gastric and colorectal cancer. Pol Przegl Chir. 2020;92(2):8–11.

    PubMed  Google Scholar 

  47. Mikamori M, Miyamoto A, Asaoka T, Maeda S, Hama N, Yamamoto K, Hirao M, Ikeda M, Sekimoto M, Doki Y, et al. Postoperative changes in body composition after Pancreaticoduodenectomy using multifrequency bioelectrical impedance analysis. J Gastrointest Surg. 2016;20(3):611–8.

    Article  PubMed  Google Scholar 

  48. Ausania F, Senra P, Meléndez R, Caballeiro R, Ouviña R, Casal-Núñez E. Prehabilitation in patients undergoing pancreaticoduodenectomy: a randomized controlled trial. Rev Esp Enferm Dig. 2019;111(8):603–8.

    PubMed  Google Scholar 

  49. Su CH, Tsay SH, Wu CC, Shyr YM, King KL, Lee CH, Lui WY, Liu TJ, P’Eng FK. Factors influencing postoperative morbidity, mortality, and survival after resection for hilar cholangiocarcinoma. Ann Surg. 1996;223(4):384–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Karunakaran M, Barreto SG. Is enhancing recovery after pancreatic cancer surgery even possible?-a narrative review. Chin Clin Oncol. 2021;10(5):49.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Editage (https://www.editage.jp/) for the English language review.

Funding

None.

Author information

Authors and Affiliations

  1. Department of Surgery, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, 3-1 Aoyama, Kure, Hiroshima, 737-0023, Japan

    Yoshiyuki Shibata, Takeshi Sudo, Sho Tazuma, Haruki Sada, Naoki Tanimine, Norimitsu Shimada, Hirofumi Tazawa, Takahisa Suzuki, Takashi Onoe, Yosuke Shimizu & Hirotaka Tashiro

  2. Department of Gastroenterology, National Hospital Organization Kure Medical Center and Chugoku Cancer Center, 3-1 Aoyama, Kure, Hiroshima, 737-0023, Japan

    Atsushi Yamaguchi

  3. Department of Surgery, Graduate School of Biochemical and Health Science, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan

    Shinya Takahashi

Authors
  1. Yoshiyuki Shibata
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Takeshi Sudo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sho Tazuma
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Haruki Sada
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Naoki Tanimine
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Norimitsu Shimada
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hirofumi Tazawa
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Takahisa Suzuki
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Takashi Onoe
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Yosuke Shimizu
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Hirotaka Tashiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Atsushi Yamaguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Shinya Takahashi
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Study conception and design: Yoshiyuki Shibata, Takeshi Sudo. Acquisition of data: Yoshiyuki Shibata, Takeshi Sudo, Sho Tazuma, Haruki Sada, Naoki Tanimine, Norimitsu Shimada, Hirofumi Tazawa, Takahisa Suzuki, Takashi Onoe, Yosuke Shimizu, Hirotaka Tashiro, Atsushi Yamaguchi. Analysis and interpretation of data: Yoshiyuki Shibata, Takeshi Sudo. Drafting of manuscript: Yoshiyuki Shibata, Takeshi Sudo. Critical revision of manuscript: Yoshiyuki Shibata, Takeshi Sudo, Shinya Takahashi.

Corresponding author

Correspondence to Yoshiyuki Shibata.

Ethics declarations

Ethics approval and consent to participate

This study was conducted following the principles of the Declaration of Helsinki and was approved by the Institutional Review Board of National Hospital Organization Kure Medical Center (2023–17). All patients provided written informed consent.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shibata, Y., Sudo, T., Tazuma, S. et al. Effect of body fat mass loss on prognosis of radical resection for pancreatic ductal adenocarcinoma based on bioelectrical impedance analysis. BMC Surg 24, 19 (2024). https://doi.org/10.1186/s12893-024-02315-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12893-024-02315-4

Keywords

BMC Surgery

ISSN: 1471-2482

Contact us