Next Article in Journal
Exosomes—Promising Carriers for Regulatory Therapy in Oncology
Next Article in Special Issue
Results of a Randomized, Double-Blind, Placebo-Controlled, Phase 1b/2 Trial of Nabpaclitaxel + Gemcitabine ± Olaratumab in Treatment-Naïve Participants with Metastatic Pancreatic Cancer
Previous Article in Journal
Predictive Value of Magnetic Resonance Imaging in Risk Stratification and Molecular Classification of Endometrial Cancer
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 16
Issue 5
10.3390/cancers16050922
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

C-Reactive Protein-to-Albumin Ratio to Predict Tolerability of S-1 as an Adjuvant Chemotherapy in Pancreatic Cancer

by
Naotake Funamizu
*,
Akimasa Sakamoto
,
Takahiro Hikida
,
Chihiro Ito
,
Mikiya Shine
,
Yusuke Nishi
,
Mio Uraoka
,
Tomoyuki Nagaoka
,
Masahiko Honjo
,
Kei Tamura
,
Katsunori Sakamoto
,
Kohei Ogawa
and
Yasutsugu Takada
Department of Hepato-Biliary-Pancreatic Surgery, Ehime University Graduate School of Medicine, Toon 791-0295, Japan
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(5), 922; https://doi.org/10.3390/cancers16050922
Submission received: 5 February 2024 / Revised: 19 February 2024 / Accepted: 23 February 2024 / Published: 25 February 2024
(This article belongs to the Special Issue Clinical Trials for Hepatobiliary and Pancreatic Cancer Diagnosis and Treatment)
Browse Figures
Review Reports Versions Notes

Abstract

:

Simple Summary

Adjuvant chemotherapy (AC) with S1 is beneficial for pancreatic cancer, but the completion rate of S1 remains at 70%. Additionally, there are no useful indicators for achieving completion of S1. Therefore, we have assumed that studying the C-reactive protein-to-albumin ratio as an indicator based on nutritional status may be useful in predicting this. When this indicator proves effective, we believe that more cases can complete the treatment by improving nutrition or adjusting the dosage before starting AC.

Abstract

Adjuvant chemotherapy (AC) with S-1 after radical surgery for resectable pancreatic cancer (PC) has shown a significant survival advantage over surgery alone. Consequently, ensuring that patients receive a consistent, uninterrupted S-1 regimen is of paramount importance. This study aimed to investigate whether the C-reactive protein-to-albumin ratio (CAR) could predict S-1 AC completion in PC patients without dropout due to adverse events (AEs). We retrospectively enrolled 95 patients who underwent radical pancreatectomy and S-1 AC for PC between January 2010 and December 2022. A statistical analysis was conducted to explore the correlation of predictive markers with S-1 completion, defined as continuous oral administration for 6 months. Among the 95 enrolled patients, 66 (69.5%) completed S-1, and 29 (30.5%) failed. Receiver operating characteristic curve analysis revealed 0.05 as the optimal CAR threshold to predict S-1 completion. Univariate and multivariate analyses further validated that a CAR ≥ 0.05 was independently correlated with S-1 completion (p < 0.001 and p = 0.006, respectively). Furthermore, a significant association was established between a higher CAR at initiation of oral administration and acceptable recurrence-free and overall survival (p = 0.003 and p < 0.001, respectively). CAR ≥ 0.05 serves as a predictive marker for difficulty in completing S-1 treatment as AC for PC due to AEs.

1. Introduction

Pancreatic cancer (PC) is a highly malignant tumor with low morbidity. Surgical resection is necessary to achieve a cure in PC. However, despite advancements in surgical techniques and perioperative management, the 5-year survival rate remains low, at only 12%. This is primarily because >90% of patients experience local recurrence or distant metastasis following radical resection [1]. Several clinical trials have yielded compelling evidence that in cases of resectable PC, combined radical resection and adjuvant chemotherapy (AC) results in a significantly improved prognosis compared to surgery alone [2,3,4]. Notably, the Japanese guidelines recommend the oral administration of S-1 as the standard AC protocol following radical surgery for PC patients with PC [5]. This recommendation is based on the findings of a randomized trial conducted by the Japan Adjuvant Study Group of Pancreatic Cancer (JASPAC01), which demonstrated that patients who received S-1 exhibited significantly longer 5-year and median survival rates than those who were administered gemcitabine following radical surgery [6]. Despite the established efficacy of AC in improving the prognosis of PC patients, achieving successful completion can be challenging because of the occurrence of postoperative complications (POCs) or adverse events (AEs) associated with the AC regimen itself [7]. However, the reported completion rates for AC due to S-1 have been suboptimal, typically falling by approximately 70% [8,9]. Discontinuation of AC regimens can compromise their anticancer effectiveness, resulting in adverse implications on patient prognosis. Hence, clinicians urgently need to identify reliable indicators for predicting the successful completion of S-1 treatment. Recent reports have suggested a potential correlation between nutritional status and treatment completion rates for AC [10,11,12]. Consequently, the primary objective of this study was to evaluate whether the C-reactive protein (CRP)-to-albumin ratio (CAR), a recognized nutritional marker, could act as a novel predictor for the rate of S-1 non-completion due to AEs in patients with PC.

2. Materials and Methods

In this retrospective study, we enrolled 186 consecutive patients who underwent radical pancreatic resection for PC at Ehime University Hospital (Toon City, Japan) between January 2010 and December 2022. Notably, 60 patients were excluded, as they did not initiate S-1 AC. Consequently, the final analysis included a cohort of 126 patients (Figure 1). It is worth highlighting that no patient mortality occurred before postoperative day 90. This study involved an extensive review of the patients’ medical records, encompassing the collection of data pertaining to patient backgrounds, perioperative laboratory results, perioperative clinical information, pathological findings, and postoperative prognoses.
During pancreatoduodenectomy, the majority of pancreatic anastomoses to the alimentary tract were carried out using the end-to-side pancreatojejunostomy technique, and as part of the routine procedure, two closed suction drainage tubes were inserted. In cases of distal pancreatectomy, pancreatic resection was predominantly accomplished using a linear stapler, and one or two closed suction drainage tubes were routinely placed, in accordance with the surgeon’s preference. To assess POCs, we applied the Clavien–Dindo (CD) classification, with grade ≥3 complications being categorized as major POCs [13].
At our hospital, AC was scheduled to commence promptly following hospital discharge and to continue for 6 months. Most patients initiated AC within 3 months of curative surgery. The therapeutic regimen included oral administration of S-1, ranging from 80 to 120 mg, contingent on body surface area, twice a day for 28 days, followed by a 14-day rest period. Treatment courses were repeated over 6 months unless intolerable toxicity occurred. Relative dose intensity (RDI) was calculated as the ratio of the actual dose intensity to the standard or planned S-1 dose intensity [14]. Completion of S-1 therapy was defined as persistent oral administration of S-1 with an RDI exceeding 80% [15,16,17]. Hematological and biochemical analyses, in conjunction with clinical parameters, including body weight fluctuations, were assessed at AC initiation and during all follow-up appointments. Postoperative surveillance was performed using contrast-enhanced CT on a monthly basis. AEs were evaluated in accordance with the Common Terminology Criteria for Adverse Events version 5.0, and AEs with grade ≥3 were categorized as severe AEs [16,18].
The CRP and albumin levels were measured on the same day, before the initiation of AC, and they were used to calculate the CAR. The timing of blood collection was determined by utilizing the blood test results taken when each surgeon considered it appropriate to commence adjuvant chemotherapy. CAR was calculated using the following formula: CAR = [CRP (mg/dL)]/[albumin (g/dL)] [17,19]. Following the determination of the CAR threshold value, patients were stratified into two groups: S-1-complete group and S-1-incomplete group.
All statistical analyses were conducted using the Statistical Package for the Social Sciences version 16.0 for Windows® (IBM Corp., Armonk, NY, USA) and GraphPad Prism version 5.0 (GraphPad Software Inc., La Jolla, CA, USA). Patient demographics are presented as medians and interquartile ranges for nonparametric distributions, whereas categorical data are presented as numbers and percentages. The statistical significance of patient demographics and outcomes was assessed using the χ2 test, Fisher’s exact test, and the U test, as appropriate. Univariate and multivariate analyses were used to identify independent factors affecting the completion of S-1 administration. To determine the optimal cutoff value for CAR in predicting the risk of S-1 incompletion, a receiver operating characteristic (ROC) curve analysis was performed, and the cutoff value was determined using the Youden index. Overall survival (OS) and recurrence-free survival (RFS) following curative surgery were evaluated using the Kaplan–Meier method, and survival curves were compared using the log-rank test. A p value < 0.05 was considered statistically significant.

3. Results

3.1. Patients Characteristics with or without S-1 Completion

During the study period, 126 patients underwent curative surgery for PC, after which they were initiated on S-1 as the AC regimen. Among these patients, 66 (69.5%) continued AC, achieving an RDI > 80%. In contrast, 31 patients experienced recurrence during AC, prompting a modification of the treatment regimen. Moreover, 24 individuals required dose reduction and/or treatment interruption owing to AEs. Four patients terminated AC due to POCs, such as cholangitis, whereas one patient discontinued treatment due to an unrelated condition (cerebral infarction) (Figure 1). The detailed patient characteristics are presented in Table 1. Additionally, laboratory test findings at the onset of AC as well as relevant AC-related factors are outlined in Table 2.
There were no differences in the initiation period of AC and carbohydrate antigen 19-9 values between the S-1-complete and S-1-non-complete groups. However, significant differences were observed in the body mass index (BMI) and CAR between the groups (p = 0.026 and p < 0.001, respectively).

3.2. Calculation of the Optimal CAR

The optimal cutoff value was determined using ROC curve analysis (Figure 2). The areas under the ROC curves for the CAR, albumin, and CRP levels were 0.806, 0.704, and 0.799, respectively. The Youden index indicated that the most appropriate cutoff value for the CAR was 0.05, with a sensitivity of 72.7%, a specificity of 82.8%, and a likelihood ratio of 4.22. Patients were stratified into two groups based on the CAR cutoff value: the higher-CAR group (CAR ≥ 0.05, n = 42) and the lower-CAR group (CAR < 0.05, n = 53). Failure of S-1 completion occurred in 24 patients (57.1%) in the higher-CAR group and in only 5 patients (9.4%) in the lower-CAR group. Univariate analysis was conducted to assess whether a CAR value ≥ 0.05 can serve as a risk factor for the failure of S-1 treatment following surgery (p < 0.001) (Table 3).

3.3. Multivariate Analysis for S-1 Completion

All predictive factors that correlated with S-1 completion on univariate analysis were included in the multivariate analysis (Table 4). In the multivariate analysis, CAR < 0.05 and BMI were identified as independent risk factors for S-1 completion (hazard ratio [HR], 12.734; 95% confidence interval [CI], 2.064–79.253; p = 0.006; and HR, 1.322; 95% CI, 1.041–1.680; p = 0.022, respectively).

3.4. CAR and Outcome

The prognostic value of the CAR was also investigated (Figure 3). Patients with CAR ≥ 0.05 had worse RFS (HR, 0.323; 95% CI, 0.155–0.671; p = 0.002) and OS (HR, 0.249; 95% CI, 0.119–0.523; p = 0.001) than patients with CAR < 0.05.

4. Discussion

S-1 is a groundbreaking oral anticancer medication meticulously crafted from tegafur, a prodrug renowned for its transformative potential into three potent chemotherapeutic agents: fluorouracil, gimeracil, and potassium oteracils. Gimeracil’s mode of action is intricately tied to its ability to inhibit the activity of dihydropyrimidine dehydrogenase, a pivotal enzyme involved in the metabolism of fluorouracil. By impeding this enzyme, gimeracil effectively boosts the levels of fluorouracil both in the bloodstream and within tumor tissues, thereby enhancing its therapeutic efficacy. Conversely, oteracil potassium, another essential component of S-1, assumes a pivotal role in the complex interplay of pharmacodynamics. It exerts its influence by actively suppressing the phosphorylation of fluorouracil within the gastrointestinal tract. This mechanism significantly mitigates the risk of gastrointestinal toxicity associated with fluorouracil administration, ensuring a more tolerable treatment experience for patients undergoing chemotherapy. The clinical efficacy of S-1 has been extensively studied and validated, particularly in the context of adjuvant chemotherapy for various cancer types. Notably, in Japanese patients diagnosed with gastric cancer, as evidenced by multiple studies [8], S-1 has exhibited remarkable efficacy in conferring survival benefits and improving overall prognosis. Similarly, in the ASCOT trial involving patients with biliary tract cancer [9], S-1 has demonstrated compelling evidence of its ability to enhance patient outcomes when used as part of a comprehensive treatment regimen. The standard treatment for PC with AC was established based on the findings of the JASPAC01 trial [6]. Although tolerance of S-1 is generally considered higher in the Asian population than in the Caucasian population, it remains a challenge for all patients [20,21]. Fundamentally, in both of the two prior large-scale trials investigating S-1 (ASCOT [9] and JASPAC01 [6]), 72% of the patients successfully completed S-1 therapy; in this study, 69.5% of the patients completed AC treatment, which is consistent with earlier findings. Owing to the high rate of treatment failure, identification of a marker to predict the completion of S-1 treatment in a non-invasive and straightforward manner would be valuable for assessing patient prognosis and postoperative follow-up intervals.
In recent years, reports have suggested that nutritional status could influence POCs [22,23,24,25,26]. Additionally, the relationship between nutritional status and prognosis has been intensively investigated in a variety of cancer types, emphasizing the significance of assessing and improving patients’ nutritional status [27,28,29,30]. Conversely, some reports have suggested that inflammation can also affect POCs and prognosis [31,32,33]. Therefore, we assumed that indicators encompassing both the nutritional status and inflammatory conditions would be more promising. Various indicators, including the lymphocyte-to-CRP ratio [34], platelet-to-albumin ratio [35], neutrophil-to-lymphocyte ratio [36,37], platelet-to-lymphocyte ratio [38], prognostic nutritional index [39,40], and CAR [41,42], which take into account both inflammation and nutritional status, have been identified as predictors of prognosis or POCs. Among these indicators, the identification of one as a useful prognostic marker may also allow us to predict the S-1 completion rates for AC, which are correlated with better prognosis in PC patients. Therefore, in the present study, we focused on the CAR as an optimal novel index to predict S-1 completion, and thereby the prognosis of PC patients. The CAR has been reported to be associated with POCs and prognosis in patients with cancer or severe infections [40,43,44]. Moreover, CAR has been suggested to be associated with POCs and prognosis of PC [45,46]. Various nutritional indicators have been studied in relation to AC tolerance due to S-1 in several types of cancers, including body weight loss [47], albumin-bilirubin score, geriatric nutritional risk index, prognostic nutritional index, and neutrophil-to-lymphocyte ratio [12,48,49].
In this study, CAR was higher in the S-1-incomplete group than in the S-1-complete group. An observed CAR value of 0.05 or greater was linked to an increased risk of S-1 therapy incompletion due to AEs, indicating that enhancing prechemotherapeutic nutritional or inflammatory status could potentially reduce the incidence of failure of S-1 treatment caused by AEs. Furthermore, a CAR value of 0.05 or higher not only serves as an indicator of the successful completion of S-1 therapy but also holds promise as a significant prognostic marker. This observation, however, is not unexpected, considering the well-established improvement in overall prognosis associated with AC utilizing S-1. Additionally, the consistency of CAR values equal to or greater than 0.05, with the CAR value previously identified as a predictive factor for POCs in a prior study involving PC patients from our institution [42], provides further validation of its prognostic relevance in the context of PC treatment.
According to a large-scale study, patients who experienced severe POCs, specifically those with a CD grade ≥3, were reported to initiate AC less frequently after pancreatic surgery [50]. Furthermore, it has been demonstrated that CAR serves as a valuable predictor of POCs following pancreatic resection [41,42]. CAR, a straightforward metric calculated solely through blood tests, has been underscored as a prognostic factor for PC patients. This result suggests the increasing importance of managing the nutritional status of patients with cancer, in addition to monitoring CAR. As mentioned above, numerous nutritional assessment indices have been documented as prognostic indicators of PC. Notably, CAR has been independently reported as a prognostic factor of PC in numerous studies [46,51,52]. Thus, our results are consistent with these findings. Furthermore, body weight loss has been reported to hinder S-1 completion [47,53], and our data indicate that a lower BMI is a predictive factor of treatment failure. Accordingly, the failure to recover postoperative weight loss prior to administering AC with S-1 suggests a heightened risk of dropout due to AEs. Given the close association between weight loss and nutritional status, this finding aligns with our data, indicating S-1 incompletion in cases with elevated CAR values.
However, this study has some limitations. First, this is a single-center study with a relatively small dataset, which may have introduced bias into the data analysis and thereby potentially limited our ability to fully assess the impact of the CAR. Second, the retrospective nature of this study may have introduced selection bias. Finally, the details of S-1 treatment, including the timing of initiation, dosage, dose reduction, and withdrawal, were determined by the physician. Moreover, in this study, an RDI > 80 was defined as S-1 completion, but the appropriateness of the cutoff value of 80 has not been conclusively determined. Therefore, the results of this study should be verified in a large-scale series.

5. Conclusions

In this groundbreaking study, we have identified a critical cutoff value for the CAR score, demonstrating that a CAR value surpassing 0.05 is associated with a decreased completion rate of AC utilizing S-1. This significant finding not only sheds light on the predictive capacity of CAR in anticipating the non-completion of S-1 treatment due to adverse AEs, but also represents a pioneering effort in this domain. The implications of this study are profound, suggesting that CAR could serve as a valuable tool for clinicians in identifying patients who are at heightened risk of encountering challenges in tolerating S-1 treatment, owing to AEs. By leveraging CAR as a predictive metric, healthcare providers can proactively intervene and tailor treatment strategies to mitigate the impact of AEs, thereby optimizing patient outcomes and treatment adherence. Building upon these findings, the research team intends to embark on prospective trials aimed at investigating the efficacy of nutritional interventions among patients exhibiting elevated CAR values. By implementing targeted interventions, the goal is to evaluate the extent to which these interventions can alleviate adverse events and enhance treatment tolerability among the approximately 30% of patients who do not complete S-1 AC treatment. In essence, this study represents a pivotal step forward in personalized cancer care, offering a novel approach to risk stratification and intervention planning. By harnessing the predictive power of CAR and exploring innovative strategies for intervention, clinicians can strive towards improving the delivery of S-1 AC and ultimately enhancing the quality of care for cancer patients.

Author Contributions

Conceptualization, N.F., A.S. and Y.T.; methodology, N.F. and T.H.; validation, C.I., M.S., M.H., K.T. and K.O.; investigation, N.F., Y.N., M.U. and T.N.; resources, M.H.; data curation, K.T.; writing—original draft preparation, N.F.; writing—review and editing, Y.T.; visualization, K.S.; supervision, K.O.; project administration, K.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, as revised in 2013, and approved by the Institutional Ethics Committee of Ehime University Hospital (no. 2311013).

Informed Consent Statement

All participants, including retrospectively registered patients or their guardians, provided informed consent for the use of their medical information for scientific research purposes.

Data Availability Statement

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

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

CARC-reactive protein-to-albumin ratio
ACAdjuvant chemotherapy
AEsAdverse events
PCPancreatic cancer
POCsPostoperative complications
CD ClassificationClavien–Dindo classification
ROCReceiver operating characteristic
OSOverall survival
RFSRecurrence-free survival
RDIRelative dose intensity

References

  1. Siegel, R.L.; Miller, K.D.; Wagle, N.S.; Jemal, A. Cancer statistics, 2023. CA Cancer J. Clin. 2023, 73, 17–48. [Google Scholar] [CrossRef]
  2. Neoptolemos, J.P.; Moore, M.J.; Cox, T.F.; Valle, J.W.; Palmer, D.H.; McDonald, A.C.; Carter, R.; Tebbutt, N.C.; Dervenis, C.; Smith, D.; et al. Effect of adjuvant chemotherapy with fluorouracil plus folinic acid or gemcitabine vs observation on survival in patients with resected periampullary adenocarcinoma: The ESPAC-3 periampullary cancer randomized trial. JAMA 2012, 308, 147–156. [Google Scholar] [CrossRef] [PubMed]
  3. Oettle, H.; Post, S.; Neuhaus, P.; Gellert, K.; Langrehr, J.; Ridwelski, K.; Schramm, H.; Fahlke, J.; Zuelke, C.; Burkart, C.; et al. Adjuvant chemotherapy with gemcitabine vs observation in patients undergoing curative-intent resection of pancreatic cancer: A randomized controlled trial. JAMA 2007, 297, 267–277. [Google Scholar] [CrossRef]
  4. Oettle, H.; Neuhaus, P.; Hochhaus, A.; Hartmann, J.T.; Gellert, K.; Ridwelski, K.; Niedergethmann, M.; Zülke, C.; Fahlke, J.; Arning, M.B.; et al. Adjuvant chemotherapy with gemcitabine and long-term outcomes among patients with resected pancreatic cancer: The CONKO-001 randomized trial. JAMA 2013, 310, 1473–1481. [Google Scholar] [CrossRef] [PubMed]
  5. Japan Pancreas Society. Clinical Practice Guidelines For Pancreatic Cancer. 2019. Available online: http://www.suizou.org/pdf/pancreatic_cancer_cpg-2019.pdf (accessed on 5 May 2023). (In Japanese).
  6. 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, 248–257. [Google Scholar] [CrossRef] [PubMed]
  7. Ueno, H.; Kosuge, T.; Matsuyama, Y.; Yamamoto, J.; Nakao, A.; Egawa, S.; Doi, R.; Monden, M.; Hatori, T.; Tanaka, M.; et al. A randomised phase III trial comparing gemcitabine with surgery-only in patients with resected pancreatic cancer: Japanese Study Group of Adjuvant Therapy for Pancreatic Cancer. Br. J. Cancer 2009, 101, 908–915. [Google Scholar] [CrossRef] [PubMed]
  8. Sakuramoto, S.; Sasako, M.; Yamaguchi, T.; Kinoshita, T.; Fujii, M.; Nashimoto, A.; Furukawa, H.; Nakajima, T.; Ohashi, Y.; Imamura, H.; et al. Adjuvant chemotherapy for gastric cancer with S-1, an oral fluoropyrimidine. N. Engl. J. Med. 2007, 357, 1810–1820. [Google Scholar] [CrossRef] [PubMed]
  9. Nakachi, K.; Ikeda, M.; Konishi, M.; Nomura, S.; Katayama, H.; Kataoka, T.; Todaka, A.; Yanagimoto, H.; Morinaga, S.; Kobayashi, S.; et al. Adjuvant S-1 compared with observation in resected biliary tract cancer (JCOG1202, ASCOT): A multicentre, open-label, randomised, controlled, phase 3 trial. Lancet 2023, 401, 195–203. [Google Scholar] [CrossRef]
  10. Yamada, D.; Eguchi, H.; Asaoka, T.; Tomihara, H.; Noda, T.; Wada, H.; Kawamoto, K.; Gotoh, K.; Takeda, Y.; Tanemura, M.; et al. The basal nutritional state of PDAC patients is the dominant factor for completing adjuvant chemotherapy. Surg. Today 2017, 47, 1361–1371. [Google Scholar] [CrossRef]
  11. Matsumoto, I.; Tanaka, M.; Shirakawa, S.; Shinzeki, M.; Toyama, H.; Asari, S.; Goto, T.; Yamashita, H.; Ishida, J.; Ajiki, T.; et al. Postoperative serum albumin level is a marker of incomplete adjuvant chemotherapy in patients with pancreatic ductal adenocarcinoma. Ann. Surg. Oncol. 2015, 22, 2408–2415. [Google Scholar] [CrossRef]
  12. Sakamoto, A.; Funamizu, N.; Shine, M.; Uraoka, M.; Nagaoka, T.; Honjo, M.; Tamura, K.; Sakamoto, K.; Ogawa, K.; Takada, Y. Geriatric nutritional risk index predicts tolerability of S-1 as adjuvant chemotherapy for pancreatic ductal adenocarcinoma. Pancreas 2023, 52, e196–e202. [Google Scholar]
  13. Dindo, D.; Demartines, N.; Clavien, P.A. Classification of surgical complications: A new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann. Surg. 2004, 240, 205–213. [Google Scholar] [CrossRef]
  14. Valle, J.W.; Palmer, D.; Jackson, R.; Cox, T.; Neoptolemos, J.P.; Ghaneh, P.; Rawcliffe, C.L.; Bassi, C.; Stocken, D.D.; Cunningham, D.; et al. Optimal duration and timing of adjuvant chemotherapy after definitive surgery for ductal adenocarcinoma of the pancreas: Ongoing lessons from the ESPAC-3 study. J. Clin. Oncol. 2014, 32, 504–512. [Google Scholar] [CrossRef]
  15. Qi, W.; Wang, X.; Gan, L.; Li, Y.; Li, H.; Cheng, Q. The effect of reduced RDI of chemotherapy on the outcome of breast cancer patients. Sci. Rep. 2020, 10, 13241. [Google Scholar] [CrossRef]
  16. Yabusaki, N.; Fujii, T.; Yamada, S.; Murotani, K.; Sugimoto, H.; Kanda, M.; Nakayama, G.; Koike, M.; Fujiwara, M.; Kodera, Y.; et al. The significance of relative dose intensity in adjuvant chemotherapy of pancreatic ductal adenocarcinoma-including the analysis of clinicopathological factors influencing relative dose intensity. Medicine 2016, 95, e4282. [Google Scholar] [CrossRef]
  17. Nielson, C.M.; Bylsma, L.C.; Fryzek, J.P.; Saad, H.A.; Crawford, J. Relative dose intensity of chemotherapy and survival in patients with advanced stage solid tumor cancer: A systematic review and meta-analysis. Oncologist 2021, 26, e1609–e1618. [Google Scholar] [CrossRef]
  18. U.S. Department of Health and Human Services. Common Terminology Criteria for Adverse Events (CTCAE); Version 5; National Cancer Institute: Bethesda, MD, USA, 2017.
  19. Fairclough, E.; Cairns, E.; Hamilton, J.; Kelly, C. Evaluation of a modified early warning system for acute medical admissions and comparison with C-reactive protein/albumin ratio as a predictor of patient outcome. Clin. Med. 2009, 9, 30–33. [Google Scholar] [CrossRef] [PubMed]
  20. Shirasaka, T.; Shimamato, Y.; Ohshimo, H.; Yamaguchi, M.; Kato, T.; Yonekura, K.; Fukushima, M. Development of a novel form of an oral 5-fluorouracil derivative (S-1) directed to the potentiation of the tumor selective cytotoxicity of 5-fluorouracil by two biochemical modulators. Anticancer Drugs 1996, 7, 548–557. [Google Scholar] [CrossRef] [PubMed]
  21. Chuah, B.; Goh, B.C.; Lee, S.C.; Soong, R.; Lau, F.; Mulay, M.; Dinolfo, M.; Lim, S.E.; Soo, R.; Furuie, T.; et al. Comparison of the pharmacokinetics and pharmacodynamics of S-1 between Caucasian and East Asian patients. Cancer Sci. 2011, 102, 478–483. [Google Scholar] [CrossRef]
  22. Menozzi, R.; Valoriani, F.; Ballarin, R.; Alemanno, L.; Vinciguerra, M.; Barbieri, R.; Cuoghi Costantini, R.; D’Amico, R.; Torricelli, P.; Pecchi, A. Impact of nutritional status on postoperative outcomes in cancer patients following elective pancreatic surgery. Nutrients 2023, 15, 1958. [Google Scholar] [CrossRef] [PubMed]
  23. Martínez-Ortega, A.J.; Piñar-Gutiérrez, A.; Serrano-Aguayo, P.; González-Navarro, I.; Remón-Ruíz, P.J.; Pereira-Cunill, J.L.; García-Luna, P.P. Perioperative nutritional support: A review of current literature. Nutrients 2022, 14, 1601. [Google Scholar] [CrossRef]
  24. Liao, C.K.; Chern, Y.J.; Hsu, Y.J.; Lin, Y.C.; Yu, Y.L.; Chiang, J.M.; Yeh, C.Y.; You, J.F. The clinical utility of the geriatric nutritional risk index in predicting postoperative complications and long-term survival in elderly patients with colorectal cancer after curative surgery. Cancers 2021, 13, 5852. [Google Scholar] [CrossRef]
  25. Funamizu, N.; Nakabayashi, Y.; Kurihara, K. Lower geriatric nutritional risk index predicts postoperative pancreatic fistula in patients with distal pancreatectomy. Mol. Clin. Oncol. 2020, 12, 134–137. [Google Scholar] [CrossRef]
  26. Funamizu, N.; Nakabayashi, Y.; Iida, T.; Kurihara, K. Geriatric nutritional risk index predicts surgical site infection after pancreaticoduodenectomy. Mol. Clin. Oncol. 2018, 9, 274–278. [Google Scholar] [CrossRef]
  27. Hayama, T.; Hashiguchi, Y.; Ozawa, T.; Watanabe, M.; Fukushima, Y.; Shimada, R.; Nozawa, K.; Matsuda, K.; Fujii, S.; Fukagawa, T. The preoperative geriatric nutritional risk index (GNRI) is an independent prognostic factor in elderly patients underwent curative resection for colorectal cancer. Sci. Rep. 2022, 12, 3682. [Google Scholar] [CrossRef]
  28. Hayama, T.; Ozawa, T.; Okada, Y.; Tsukamoto, M.; Fukushima, Y.; Shimada, R.; Nozawa, K.; Matsuda, K.; Fujii, S.; Hashiguchi, Y. The pretreatment Controlling Nutritional Status (CONUT) score is an independent prognostic factor in patients undergoing resection for colorectal cancer. Sci. Rep. 2020, 10, 13239. [Google Scholar] [CrossRef]
  29. Trestini, I.; Carbognin, L.; Sperduti, I.; Bonaiuto, C.; Auriemma, A.; Melisi, D.; Salvatore, L.; Bria, E.; Tortora, G. Prognostic impact of early nutritional support in patients affected by locally advanced and metastatic pancreatic ductal adenocarcinoma undergoing chemotherapy. Eur. J. Clin. Nutr. 2018, 72, 772–779. [Google Scholar] [CrossRef] [PubMed]
  30. Funamizu, N.; Sakamoto, A.; Utsunomiya, T.; Uraoka, M.; Nagaoka, T.; Iwata, M.; Ito, C.; Tamura, K.; Sakamoto, K.; Ogawa, K.; et al. Geriatric nutritional risk index as a potential prognostic marker for patients with resectable pancreatic cancer: A single-center, retrospective cohort study. Sci. Rep. 2022, 12, 13644. [Google Scholar] [CrossRef] [PubMed]
  31. Andersen, B.L.; Myers, J.; Blevins, T.; Park, K.R.; Smith, R.M.; Reisinger, S.; Carbone, D.P.; Presley, C.J.; Shields, P.G.; Carson, W.E. Depression in association with neutrophil-to-lymphocyte, platelet-to-lymphocyte, and advanced lung cancer inflammation index biomarkers predicting lung cancer survival. PLoS ONE 2023, 18, e0282206. [Google Scholar] [CrossRef] [PubMed]
  32. Şahin, A.B.; Cubukcu, E.; Ocak, B.; Deligonul, A.; Oyucu Orhan, S.; Tolunay, S.; Gokgoz, M.S.; Cetintas, S.; Yarbas, G.; Senol, K.; et al. Low pan-immune-inflammation-value predicts better chemotherapy response and survival in breast cancer patients treated with neoadjuvant chemotherapy. Sci. Rep. 2021, 11, 14662. [Google Scholar] [CrossRef] [PubMed]
  33. Platt, J.J.; Ramanathan, M.L.; Crosbie, R.A.; Anderson, J.H.; McKee, R.F.; Horgan, P.G.; McMillan, D.C. C-reactive protein as a predictor of postoperative infective complications after curative resection in patients with colorectal cancer. Ann. Surg. Oncol. 2012, 19, 4168–4177. [Google Scholar] [CrossRef]
  34. Yamamoto, T.; Fukuda, M.; Okuchi, Y.; Oshimo, Y.; Nishikawa, Y.; Hisano, K.; Kawai, T.; Iguchi, K.; Okuda, Y.; Kamimura, R.; et al. Clinical impact of lymphocyte/C-reactive protein ratio on postoperative outcomes in patients with rectal cancer who underwent curative resection. Sci. Rep. 2022, 12, 17136. [Google Scholar] [CrossRef]
  35. Huang, Z.; Zheng, Q.; Yu, Y.; Zheng, H.; Wu, Y.; Wang, Z.; Liu, L.; Zhang, M.; Liu, T.; Li, H.; et al. Prognostic significance of platelet-to-albumin ratio in patients with esophageal squamous cell carcinoma receiving definitive radiotherapy. Sci. Rep. 2022, 12, 3535. [Google Scholar] [CrossRef]
  36. Popowicz, N.; Cheah, H.M.; Gregory, C.; Miranda, A.; Dick, I.M.; Lee, Y.C.G.; Creaney, J. Neutrophil-to-lymphocyte ratio in malignant pleural fluid: Prognostic significance. PLoS ONE 2021, 16, e0250628. [Google Scholar] [CrossRef]
  37. Shao, B.; Liu, X.; Li, H.; Song, G.; Di, L.; Jiang, H.; Yan, Y.; Zhang, R.; Ran, R.; Zhang, J.; et al. Prognostic value of pretreatment neutrophil-to-lymphocyte ratio in HER2-positive metastatic breast cancer. Curr. Oncol. 2022, 29, 6154–6166. [Google Scholar] [CrossRef]
  38. Zhang, H.; Gao, L.; Zhang, B.; Zhang, L.; Wang, C. Prognostic value of platelet to lymphocyte ratio in non-small cell lung cancer: A systematic review and meta-analysis. Sci. Rep. 2016, 6, 22618. [Google Scholar] [CrossRef] [PubMed]
  39. Ishiguro, T.; Aoyama, T.; Ju, M.; Kazama, K.; Fukuda, M.; Kanai, H.; Sawazaki, S.; Tamagawa, H.; Tamagawa, A.; Cho, H.; et al. Prognostic nutritional index as a predictor of prognosis in postoperative patients with gastric cancer. In Vivo 2023, 37, 1290–1296. [Google Scholar] [CrossRef]
  40. Ichikawa, K.; Mizuno, S.; Hayasaki, A.; Kishiwada, M.; Fujii, T.; Iizawa, Y.; Kato, H.; Tanemura, A.; Murata, Y.; Azumi, Y.; et al. Prognostic nutritional index after chemoradiotherapy was the strongest prognostic predictor among biological and conditional factors in localized pancreatic ductal adenocarcinoma patients. Cancers 2019, 11, 514. [Google Scholar] [CrossRef] [PubMed]
  41. Funamizu, N.; Utsunomiya, T.; Honjo, M.; Ito, C.; Shine, M.; Uraoka, M.; Nagaoka, T.; Tamura, K.; Sakamoto, K.; Ogawa, K.; et al. Preoperative C-reactive protein-to-albumin ratio predicts postoperative pancreatic fistula following pancreatoduodenectomy: A single-center, retrospective study. Curr. Oncol. 2022, 29, 9867–9874. [Google Scholar] [CrossRef] [PubMed]
  42. Funamizu, N.; Sogabe, K.; Shine, M.; Honjo, M.; Sakamoto, A.; Nishi, Y.; Matsui, T.; Uraoka, M.; Nagaoka, T.; Iwata, M.; et al. Association between the preoperative C-reactive protein-to-albumin ratio and the risk for postoperative pancreatic fistula following distal pancreatectomy for pancreatic cancer. Nutrients 2022, 14, 5277. [Google Scholar] [CrossRef] [PubMed]
  43. Utsumi, M.; Aoki, H.; Nagahisa, S. Preoperative C-reactive protein/albumin ratio as a predictive factor for gallbladder carcinoma. In Vivo 2020, 34, 1901–1908. [Google Scholar] [CrossRef] [PubMed]
  44. Zhou, W.; Zhang, G.L. C-reactive protein to albumin ratio predicts the outcome in renal cell carcinoma: A meta-analysis. PLoS ONE 2019, 14, e0224266. [Google Scholar] [CrossRef] [PubMed]
  45. Neumann, C.C.M.; Schneider, F.; Hilfenhaus, G.; Vecchione, L.; Felsenstein, M.; Ihlow, J.; Geisel, D.; Sander, S.; Pratschke, J.; Stintzing, S.; et al. Inflammation-based prognostic scores in pancreatic cancer patients—A single-center analysis of 1294 patients within the last decade. Cancers 2023, 15, 2367. [Google Scholar] [CrossRef]
  46. Haruki, K.; Shiba, H.; Shirai, Y.; Horiuchi, T.; Iwase, R.; Fujiwara, Y.; Furukawa, K.; Misawa, T.; Yanaga, K. The C-reactive protein to albumin ratio predicts long-term outcomes in patients with pancreatic cancer after pancreatic resection. World J. Surg. 2016, 40, 2254–2260. [Google Scholar] [CrossRef] [PubMed]
  47. Aoyama, T.; Yoshikawa, T.; Shirai, J.; Hayashi, T.; Yamada, T.; Tsuchida, K.; Hasegawa, S.; Cho, H.; Yukawa, N.; Oshima, T.; et al. Body weight loss after surgery is an independent risk factor for continuation of S-1 adjuvant chemotherapy for gastric cancer. Ann. Surg. Oncol. 2013, 20, 2000–2006. [Google Scholar] [CrossRef]
  48. Miwa, T.; Kanda, M.; Tanaka, C.; Kobayashi, D.; Hayashi, M.; Yamada, S.; Nakayama, G.; Koike, M.; Kodera, Y. Albumin-bilirubin score predicts tolerability to adjuvant S-1 monotherapy after curative gastrectomy. J. Gastric Cancer 2019, 19, 183–192. [Google Scholar] [CrossRef]
  49. Takagi, K.; Inoue, Y.; Oba, A.; Ono, Y.; Sato, T.; Ito, H.; Saino, Y.; Saiura, A.; Takahashi, Y. Impact of sarcopenia on S1 adjuvant chemotherapy and prognosis in pancreatic cancer patients. BioSci. Trends 2023, 17, 310–317. [Google Scholar] [CrossRef]
  50. Russell, T.B.; Labib, P.L.; Ausania, F.; Pando, E.; Roberts, K.J.; Kausar, A.; Mavroeidis, V.K.; Marangoni, G.; Thomasset, S.C.; Frampton, A.E.; et al. Serious complications of pancreatoduodenectomy correlate with lower rates of adjuvant chemotherapy: Results from the recurrence after Whipple’s (RAW) study. Eur. J. Surg. Oncol. 2023, 49, 106919. [Google Scholar] [CrossRef]
  51. Vujic, J.; Marsoner, K.; Wienerroither, V.; Mischinger, H.J.; Kornprat, P. The predictive value of the CRP-to-albumin ratio for patients with pancreatic cancer after curative resection: A retrospective single center study. In Vivo 2019, 33, 2071–2078. [Google Scholar] [CrossRef]
  52. Murakawa, M.; Yamamoto, N.; Kamioka, Y.; Kamiya, M.; Kobayashi, S.; Ueno, M.; Morimoto, M.; Atsumi, Y.; Aoyama, T.; Tamagawa, H.; et al. Clinical implication of pre-operative C-reactive protein-albumin ratio as a prognostic factor of patients with pancreatic ductal adenocarcinoma: A single-institutional retrospective study. In Vivo 2020, 34, 347–353. [Google Scholar] [CrossRef]
  53. Morita, Y.; Sakaguchi, T.; Kitajima, R.; Furuhashi, S.; Kiuchi, R.; Takeda, M.; Hiraide, T.; Shibasaki, Y.; Kikuchi, H.; Konno, H.; et al. Body weight loss after surgery affects the continuity of adjuvant chemotherapy for pancreatic cancer. BMC Cancer 2019, 19, 416. [Google Scholar] [CrossRef] [PubMed]
Cancers 16 00922 g001
Figure 1. Flowchart of patient selection. Arrows: inclusion criteria, dashed arrows: exclusion criteria, colored box: analyzed patients.
Figure 1. Flowchart of patient selection. Arrows: inclusion criteria, dashed arrows: exclusion criteria, colored box: analyzed patients.
Cancers 16 00922 g001
Cancers 16 00922 g002
Figure 2. Cutoff selection for C-reactive protein-to-albumin ratio (CAR) using receiver operating characteristic (ROC) curve analysis. Dashed line: Diagonal.
Figure 2. Cutoff selection for C-reactive protein-to-albumin ratio (CAR) using receiver operating characteristic (ROC) curve analysis. Dashed line: Diagonal.
Cancers 16 00922 g002
Cancers 16 00922 g003
Figure 3. Recurrence-free survival and overall survival according to the CAR cutoff value for pancreatic cancer patients.
Figure 3. Recurrence-free survival and overall survival according to the CAR cutoff value for pancreatic cancer patients.
Cancers 16 00922 g003
Table 1. Patient characteristics and perioperative data in the S-1-complete and S-1-incomplete groups.
Table 1. Patient characteristics and perioperative data in the S-1-complete and S-1-incomplete groups.
Patient CharacteristicsS-1-Complete Group (n = 66)S-1-Incomplete Group (n = 29)p Value
Sex (male)26 (39.4)17 (58.6)0.113
Age (years)68.8 (47–84)71.3 (56–85)0.191
Body mass index (kg/m2)22.6 ± 0.421.6 ± 0.60.129
ASA-classification 0.054
 1 or 263 (95.5)24 (82.8)
 33 (4.5)5 (17.2)
Neoadjuvant chemotherapy24 (36.4)9 (31.0)0.649
Operation methods
 DP27 (40.9)9 (31.0)
 PD35 (53.0)14 (65.5)
 TP4 (6.1)1 (3.5)
Operation time (min)482.1 ± 20.3533.8 ± 33.60.17
Estimated blood loss (mL)659.6 ± 72.8883.2 ± 126. 0.116
CD classification grade ≥320 (30.3)5 (17.2)0.183
Postoperative hospital stay (days)30.0 ± 2.529.9 ± 4.50.979
Pathological stage
 111 (16.7)3 (10.3)
 253 (80.3)25 (86.2)
 31 (1.5)0 (0.0)
 41 (1.5)1 (3.4)
Data are presented as n (%), median [interquartile range], or mean ± standard deviation. DP: distal pancreatectomy; PD: pancreatoduodenectomy; TP: total pancreatectomy.
Table 2. Results of blood tests at initiation of AC, perioperative factors, and AE incidence in the S-1-complete and S-1-incomplete groups.
Table 2. Results of blood tests at initiation of AC, perioperative factors, and AE incidence in the S-1-complete and S-1-incomplete groups.
VariablesS-1-Complete Group (n = 66)S-1-Incomplete Group (n = 29)p Value
Duration to AC initiation (days)51.5 ± 4.649.3 ± 4.50.777
Data at the onset of AC
   Body mass index (kg/m2)21.2 ± 0.319.8 ± 0.60.026
   Alb (mg/dL)3.8 ± 0.03.3 ± 0.10.002
   CRP (mg/dL)0.2 ± 0.21.0 ± 0.3<0.001
   CEA (ng/mL)2.5 ± 0.22.8 ± 0.40.438
   CA19-9 (U/mL)57.8 ± 29.745.2 ± 14.20.784
   CAR0.04 ± 0.010.31 ± 0.10<0.001
Severe AEs5 (7.6%)14 (48.3%)<0.001
Recurrence after S-1 treatment29 (43.9%)17 (58.6%)0.265
Data are presented as mean ± standard deviation or n (%). AC: adjuvant chemotherapy; Alb: albumin; CRP: C-reactive protein; CEA: carcinoembryonic antigen; CA19-9: carbohydrate antigen 19-9; CAR: CRP-to-albumin ratio; AEs: adverse events.
Table 3. Patient characteristics and perioperative factors in the higher-CAR (CAR ≥ 0.05) and lower- CAR (CAR < 0.05) groups.
Table 3. Patient characteristics and perioperative factors in the higher-CAR (CAR ≥ 0.05) and lower- CAR (CAR < 0.05) groups.
VariablesCAR < 0.05 (n = 53)CAR ≥ 0.05 (n = 42)p Value
Sex (male)17 (32.1)26 (61.9)0.007
Age (years)69.6 ± 1.269.6 ± 1.40.937
POCs (CD classification grade ≥3)10 (18.9)15 (35.7)0.064
Data at the onset of AC25 (46.3)5 (21.7)
  Alb (mg/dL)3.8 ± 0.13.4 ± 0.1<0.001
  CRP (mg/dL)0.06 ± 0.010.84 ± 0.20<0.001
  CA19-9 (U/mL)78.3 ± 38.024.7 ± 5.60.204
AC completion rate (%)48 (90.6)18 (42.9)<0.001
Pathological stage
  111 (20.8)3 (7.1)
  241 (77.4)37 (88.1)
  30 (0.0)1 (2.4)
  41 (1.9)1 (2.4)
Severe AEs7 (13.2)12 (28.6)0.075
Data are presented as n (%) or mean ± standard deviation. AC: adjuvant chemotherapy; POCs: postoperative complications.
Table 4. Logistic regression multivariate analysis for S-1 completion.
Table 4. Logistic regression multivariate analysis for S-1 completion.
VariablesHazard Ratio (95% Confidence Interval)p Value
BMI < 20.01.322 (1.041–1.680)0.022
Albumin < 3.43.282 (1.041–1.680)0.13
CRP > 0.181.322 (0.704–15.304)0.891
Severe AEs19.897 (3.660–108.157)<0.001
CAR > 0.0512.734 (2.064–79.253)0.006
BMI: body mass index; CRP: C-reactive protein; AEs: adverse events; CAR: CRP-to-albumin ratio.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Funamizu, N.; Sakamoto, A.; Hikida, T.; Ito, C.; Shine, M.; Nishi, Y.; Uraoka, M.; Nagaoka, T.; Honjo, M.; Tamura, K.; et al. C-Reactive Protein-to-Albumin Ratio to Predict Tolerability of S-1 as an Adjuvant Chemotherapy in Pancreatic Cancer. Cancers 2024, 16, 922. https://doi.org/10.3390/cancers16050922

AMA Style

Funamizu N, Sakamoto A, Hikida T, Ito C, Shine M, Nishi Y, Uraoka M, Nagaoka T, Honjo M, Tamura K, et al. C-Reactive Protein-to-Albumin Ratio to Predict Tolerability of S-1 as an Adjuvant Chemotherapy in Pancreatic Cancer. Cancers. 2024; 16(5):922. https://doi.org/10.3390/cancers16050922

Chicago/Turabian Style

Funamizu, Naotake, Akimasa Sakamoto, Takahiro Hikida, Chihiro Ito, Mikiya Shine, Yusuke Nishi, Mio Uraoka, Tomoyuki Nagaoka, Masahiko Honjo, Kei Tamura, and et al. 2024. "C-Reactive Protein-to-Albumin Ratio to Predict Tolerability of S-1 as an Adjuvant Chemotherapy in Pancreatic Cancer" Cancers 16, no. 5: 922. https://doi.org/10.3390/cancers16050922

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop