Research ArticleClinical Studies

The Geriatric Nutritional Risk Index as a Prognosis Predictor in Patients With Rectal Cancer Receiving Neoadjuvant Chemotherapy

SOICHIRO MINAMI, NORIKATSU MIYOSHI, SHIKI FUJINO, SHINYA KATO, YUKI SEKIDO, TSUYOSHI HATA, TAKAYUKI OGINO, HIDEKAZU TAKAHASHI, MAMORU UEMURA, HIROFUMI YAMAMOTO, YUICHIRO DOKI and HIDETOSHI EGUCHI
Anticancer Research July 2022, 42 (7) 3759-3766; DOI: https://doi.org/10.21873/anticanres.15866

Abstract

Background/Aim: There are few reports on the clinical significance of the geriatric nutritional risk index (GNRI) in patients with locally advanced rectal cancer who undergo preoperative chemotherapy (NAC, neoadjuvant chemotherapy) followed by radical resection; this study examined the relationship between preoperative GNRI, postoperative complications, and prognosis in these patients. Patients and Methods: Fifty-seven patients with rectal cancer who underwent radical resection after NAC at Osaka University Hospital between November 2011 and May 2018 were included. The GNRI was calculated as follows: GNRI= [1.489×serum albumin level (g/l)]+[41.7×present/ideal body weight (kg)]. Patients were classified into high (GNRI ≥96.74; n=36) and low GNRI (GNRI <96.74; n=21) groups, based on the results of the receiver operating characteristic curve analysis. Results: The Kaplan–Meier analysis showed that the low GNRI group had a significantly poorer cancer-specific survival (CSS) and a poorer overall survival tendency than the high GNRI group. In the univariate analysis, venous invasion, lymphatic vessel invasion, and low GNRI were significantly correlated with CSS; depth of tumor invasion, lymph node metastasis, and lymphatic vessel invasion were significantly correlated with disease-free survival (DFS). In the multivariate analysis, there were no significantly poor prognostic factors for CSS and DFS. Conclusion: Preoperative GNRI may be a useful predictor for recurrence and poor prognosis in elderly patients with rectal cancer who undergo radical resection after NAC. Further studies and accumulation of cases should investigate the relationship between preoperative GNRI and prognosis after NAC in elderly patients.

Key Words:

Malnutrition is reportedly related to cancer prognosis, and various indices have been used to measure this relationship (1). Bouillanne et al. reported that the geriatric nutritional risk index (GNRI), which is based on serum albumin levels (ALB), present body weight (PBW), and ideal body weight (IBW), is a simple nutritional screening tool for predicting the risk of nutrition-related complications and mortality in elderly patients (2).

It has been reported that the GNRI is a useful predictor of recurrence and mortality after radical resection in elderly patients with colorectal cancer (3). In addition, it has been reported that preoperative GNRI is associated with postoperative complications and prognosis not only in elderly patients but also in patients with hematological tumors and solid tumors (4-6). In recent years, curative resection after preoperative treatment for locally advanced rectal cancer has been performed; the expected outcome is tumor reduction. However, clinical trials are still underway.

There are few studies on the clinical significance of GNRI in patients who undergo radical surgery after preoperative chemotherapy [neoadjuvant chemotherapy (NAC)] for locally advanced rectal cancer. In this study, we examined the relationship between preoperative GNRI, postoperative complications, and prognosis in patients with rectal cancer who underwent radical resection after NAC.

Patients and Methods

Patients and datasets. Patients with rectal cancer who underwent rectal resection or rectal amputation after NAC were retrospectively selected from 370 patients with rectal cancer who underwent surgery at Osaka University Hospital between November 2011 and May 2018. Patient exclusion criteria were: 1) recurrent surgery, 2) multiple primary cancers, 3) preoperative chemoradiation, 4) transanal endoscopic microsurgery, and 5) insufficient pathological findings or preoperative laboratory data.

We collected the following information from the patients’ medical records: clinicopathological factors such as age, sex, body mass index (BMI), albumin (ALB), white blood cell count, C-reactive protein (CRP), carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), location of primary tumor, distant metastasis, pathological findings, and postoperative complications.

Preoperative blood samples, height, and weight were measured within 7 days before surgery. Clinicopathological factors were classified according to the 8th edition Union for International Cancer Control Tumor–Node–Metastasis (TNM) classification (7). Postoperative complications were classified using the Clavien– Dindo (CD) classification; only patients with CD Grade ≥II were included in this study (8).

All patients were followed up postoperatively according to the Japanese treatment guidelines. Tumor markers (CEA and CA19-9) were evaluated every 3 months. Computed tomography was performed every 3-6 months, while colonoscopy was performed every 1 to 2 years.

Nutritional assessment using GNRI. The GNRI, calculated using ALB, present body weight (PBW), and ideal body weight (IBW), is a simple screening tool for nutrition-related complications and mortality in elderly patients. The IBW was calculated as follows: IBW=(height in meters)2 ×22. The formula for GNRI was obtained from previous reports; it was as follows: GNRI=[1.489×serum albumin level (g/l)]+[41.7×PBW/IBW (kg)] (2). We classified patients into two groups according to the receiver operating characteristic (ROC) curve analysis based on complications (CD grade ≥III).

Statistical analysis. Continuous variables were expressed as means±standard deviation values. Differences in clinicopathological factors and complications between the GNRI groups were analyzed using the chi-square test or Fisher’s exact test. Continuous variables with parametric distributions were analyzed using Student’s t-test or analysis of variance.

Overall survival (OS), disease-free survival (DFS), and cancerspecific survival (CSS) curves were plotted using the Kaplan–Meier method and compared using the generalized log-rank test.

Univariate and multivariate analyses were performed using a Cox proportional hazards regression model to identify independent risk factors for CSS and DFS (9). Statistical significance was defined as two-sided p<0.05. All statistical analyses were performed using JMP software version 16 (SAS Institute Inc., Cary, NC, USA).

Ethical review. This study was approved by the Research Ethics Committee of Osaka University (approval number: No. 15144-6) and was conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from all the study participants.

Results

Patient characteristics. Thirty-four (59.6%) men and 23 (40.4%) women were enrolled into the study. The median age was 64 years (range=40-79 years). Twenty (35.1%), nine (15.8%), 20 (35.1%), and eight (13.3%) patients had tumors with pathological stages I, II, III, and IV, respectively. The patients with Stage IV tumors had liver metastases, lung metastases, extra-regional lymph node metastases, and peritoneal dissemination. Thirty (50.6%) patients had CD Grade ≥II postoperative complications, of whom 9 (15.8%) had CD Grade ≥III complications.

Distribution and classification of the GNRI. The overall mean preoperative GNRI was 98.9±7.9. There were no differences in the preoperative GNRI distribution according to sex and age (>65 years or <65 years of age) (Figure 1). The mean GNRI was 99.0±8.2 in men and 98.6±7.6 in women. There was no significant difference in the preoperative GNRI between the sexes (p=0.820) (Figure 1A).

Figure 1.
Figure 1.

Distribution of the geriatric nutritional risk index (GNRI) according to (A) sex (male or female) and (B) age (over 65 or under 65).

Given that the GNRI is used for the nutritional assessment of elderly patients (>65 years) and has been reported to be associated with postoperative complications and prognosis, we compared the two groups (over 65 and under 65). The mean GNRI values were 97.5±6.8 and 99.9±8.6 for the over 65 and under 65 groups, respectively. There was no significant difference in the preoperative GNRI between the two groups (p=0.196) (Figure 1B).

The GNRI was first reported by Bouillanne et al. They classified elderly patients into four groups: a no-risk group (GNRI >98), a low-risk group (GNRI: 92-98), a moderate-risk group (GNRI: 82-92), and a high-risk group (GNRI <82). The ROC curve analysis of postoperative complications (CD Grade ≥III) showed that the optimal preoperative GNRI cutoff value was 96.74 (area under the curve=0.539, sensitivity=0.889, specificity=0.417) (Figure 2).

Figure 2.
Figure 2.

Receiver operating characteristic (ROC) curve analysis of the geriatric nutritional risk index (GNRI) for postoperative complications (Clavien–Dindo Grade ≥III) in elderly patients with rectal cancer.

Based on previous studies and the ROC analysis, we classified patients into a high GNRI (GNRI ≥96.74) group (36 patients, 63.2%) and a low GNRI (GNRI <96.74) group (21 patients, 36.8%), instead of the four classifications of Bouillanne et al. The relationship between GNRI status and clinicopathological factors in the entire study population is shown in Table I.

View this table:
Table I.

The relationship between geriatric nutritional risk index (GNRI) status and clinicopathological factors in all patients.

There were no significant differences in age, sex, preoperative CEA, preoperative CA19-9, degree of differentiation, depth of tumor invasion, distant metastasis, venous invasion, TNM stage, CD Grade ≥II postoperative complications, and CD Grade ≥III postoperative complications between the high and low GNRI groups. However, there were significant differences in BMI, preoperative ALB, preoperative CRP, lymph node metastasis, and lymphatic vessel invasion between the two groups.

Postoperative complications (CD Grade ≥II) (Table II). Thirty patients had CD Grade ≥II postoperative complications. The complications included dysuria (12 patients), ileus (6 patients), catheter infection (4 patients), anastomotic leakage (3 patients), compartment syndrome (2 patients), surgical site infection (2 patients), neuropathy (2 patients), postoperative bleeding (1 patient), urinary tract infection (1 patient), and others (6 patients). The occurrence of surgical site infection tended to be higher in the low GNRI group than in the high GNRI group (p=0.066).

View this table:
Table II.

The relationship between geriatric nutritional risk index (GNRI) status and. postoperative complications (Clavien–Dindo Grades ≥II and ≥III).

Survival analysis and poor prognostic factors. The median follow-up duration was 54.1 months (range=3.8-110.8 months). We examined OS, CSS, and DFS in the survival analysis. OS tended to be significantly worse in the low GNRI group than in the high GNRI group (p=0.068). CSS was worse in the low GNRI group than in the high GNRI group (p=0.017). In contrast, DFS was not significantly different between the two groups (Figure 3).

Figure 3.
Figure 3.

Kaplan–Meier analyses of overall survival (OS), cancer-specific survival (CSS), and disease-free survival (DFS) according to geriatric nutritional risk index (GNRI).

The results of the univariate and multivariate analyses of the clinicopathological factors for CSS and DFS are found in Table III and Table IV. In the univariate analysis, venous invasion (p=0.032), lymphatic vessel invasion (p=0.039), and low GNRI (p=0.046) were risk factors for poor CSS.

View this table:
Table III.

Univariate and multivariate analyses of prognostic factors for cancer-specific survival (CSS).

View this table:
Table IV.

Univariate and multivariate analyses of prognostic factors for disease-free survival (DFS).

In the multivariate analyses using a Cox proportional hazards model, no independent prognostic risk factor for CSS was identified. Similarly, in the univariate analysis, depth of tumor invasion (T3 and T4) (p=0.030), lymph node metastasis (p<0.001), and lymphatic vessel invasion (p=0.003) were risk factors for poor DFS. In the multivariate analyses using the Cox proportional hazards model, no independent prognostic risk factor for DFS was identified.

Discussion

Our results showed that preoperative GNRI was associated with prognosis and may be a useful marker in patients with locally advanced rectal cancer who undergo radical resection after NAC.

Malnutrition is a significant risk factor for postoperative complications and mortality in patients with malignant tumors and has been reported to be associated with prognosis (10, 11). Some nutritional indices, such as the prognostic nutritional index, platelet-lymphocyte ratio, and modified Glasgow prognostic score, have been used to predict postoperative complications and long-term prognosis of cancer (12-15).

Buzby et al. reported that the nutritional risk index (NRI), which is calculated using ALB, PBW, and normal body weight, is used to estimate the association between nutritional status and postoperative complications (16, 17). However, the NRI is difficult to assess in elderly patients because they do not remember their usual body weight often (18). Bouillanne et al. changed the actual weight to IBW in the NRI formula. They reported that the GNRI is a simple screening tool for predicting the nutrition-related risk of complications and mortality in elderly patients specifically (2).

There are tools for assessing nutritional status, such as BMI, sarcopenia, PNI, and subjective global assessment. These tools have been reported to be associated with cancer prognosis, but optimal cut-off values are still debated (19-22).

Additionally, subjective global assessment is based on many subjective factors that require expertise. For example, some studies have examined the usefulness of sarcopenia in relation to postoperative complications and cancer prognosis (23-25). Sarcopenia is a useful tool for evaluating nutritional status, but its measurement is complex.

GNRI is an objective and simple prediction tool. It is calculated using only ALB, height, and body weight, which are usually measured on admission for most patients. The iliopsoas muscle area (cm2) is used to assess sarcopenia. Shoji et al. reported a correlation between the iliopsoas muscle area at the third lumbar vertebral level and GNRI score (26).

Cereda et al. reported an association between GNRI and mid-upper arm muscle circumference, arm muscle area, handgrip strength, and handgrip strength/arm muscle area (27). Therefore, the GNRI may be a useful predicting tool for postoperative complications and prognosis, especially in patients in whom assessing sarcopenia is difficult or in institutions lacking measuring equipment.

The GNRI was proposed and has been widely used for nutritional assessment in elderly patients aged ≥65 years with heart failure (28), chronic renal failure on hemodialysis (29), and chronic obstructive pulmonary disease (30) and has been reported to be significantly correlated with ALB, prealbumin, body weight, and BMI (2).

The GNRI is a recently confirmed useful predictor of morbidity and mortality in patients with cancer (3). Li et al. reported an association between low GNRI and severe postoperative complications including liver failure and poor OS, in elderly patients with hepatocellular carcinoma (31). Kushiyama et al. reported that a GNRI<92 was a risk factor for postoperative complications in elderly patients with gastric cancer (32). Bo et al. reported that a GNRI≤98 was a potential indicator of poor survival in elderly patients with esophageal cancer treated with radiotherapy (33). Miyake et al. also reported that the GNRI could be a prognosis predictor in elderly patients with non-metastatic renal cell carcinoma, and that those with a GNRI≤98 had a significantly worse CSS than other patients (6). Sasaki et al. reported that patients with colorectal cancer aged ≥65 years after curative surgery having a preoperative GNRI ≤98 had more postoperative complications and a poorer prognosis (3). Iguchi et al. reported that patients with liver metastasis of colorectal cancer had poor prognosis in the group of GNRI ≤98 (34).

There are various studies on GNRI cut-off values. Some studies used the modified GNRI classification according to the complications (32, 35), survival (6, 33), and hospitalization (8), and others used the four-group classification suggested by Bouillanne et al. (2). There are no reports on NAC cases, but postoperative complications in patients with colorectal cancer have been reported to be associated with poor oncologic outcomes, even if they are mild or moderate (CD Grade II) (36).

However, owing to the small number of cases in this study, we considered CD Grade ≥III complications. This is because the number of cases in our study was small, and if we considered moderate complications (CD Grade II), more than half of the patients would be considered as having postoperative complications. Therefore, we determined a new cut-off from the ROC curve based on postoperative complications (CD Grade ≥III).

It has been reported that the GNRI may be a useful indicator not only for elderly patients. There was no significant difference in the preoperative GNRI between the two groups (over 65 or under 65 years), suggesting that the GNRI was not biased by age.

Low ALB levels have been shown to be correlated with poor cancer prognosis in many studies (37). ALB is a known indicator of nutritional status (38), and malnutrition impairs several functions, including immunity, gastrointestinal function, and wound healing (39). The absence of these functions increases the risk of infection and postoperative complications (40, 41), and immunosuppressive conditions lead to inadequate anti-tumor immunological reactions (42, 43).

Furthermore, it has been reported that ALB is influenced by inflammation (38), and systemic inflammation is associated with a poor cancer prognosis (44). BMI is also widely used in clinical practice as an indicator to assess nutritional status and has been reported to be associated with cancer prognosis (45). Thus, we suggest that the GNRI, which combines ALB and body weight, may predict nutrition-related risk better than ALB alone.

There are limitations to our study. First, this study was a retrospective study with a small sample size and few participating institutions, making it subject to several selection and information biases. Prospective multicenter studies should be performed in the future. Second, we adapted the GNRI to patients below 65 years of age in this study. In the future, we will accumulate cases and examine the usefulness of the GNRI in elderly patients. In addition, we will examine a new prediction formula for the GNRI according to age. Third, this study showed that the NAC course and regimen were not uniform, and the time intervals between NAC and surgery were not similar. We predict that patients with rectal cancer who undergo radical resection after NAC will increase, hence the need to unify our NAC courses and regimens.

To conclude, we identified GNRI as a significant marker of poor prognosis in patients with locally advanced colorectal cancer who underwent NAC followed by radical resection. We will continue to examine preoperative GNRI and prognosis after NAC in elderly patients.

Acknowledgements

The Authors are grateful to Aayaka Tojo and Aya Ito for helping with this study.

Footnotes

  • Authors’ Contributions

    S.M., N.M., S.F., Y.D., and H.E. contributed to the conception and design of this study. S.M., N.M., and S.F. collected, analyzed, and interpreted the data. S.M., N.M., and S.F. wrote the manuscript. S.M., S.K., Y.S., T.H., T.O., H.T., M.U., and H.Y. followed up the clinical data. All Authors discussed the results and approved the manuscript.

  • Conflicts of Interest

    The Authors declare no competing interests in relation to this study.

  • Received May 18, 2022.
  • Revision received June 13, 2022.
  • Accepted June 14, 2022.

References

  1. ↵
    2. Bullock AF ,
    3. Greenley SL ,
    4. McKenzie GAG ,
    5. Paton LW and
    6. Johnson MJ
    : Relationship between markers of malnutrition and clinical outcomes in older adults with cancer: systematic review, narrative synthesis and meta-analysis. Eur J Clin Nutr 74(11): 1519-1535, 2020. PMID: 32366995. DOI: 10.1038/s41430-020-0629-0
    OpenUrlCrossRefPubMed
  2. ↵
    2. Bouillanne O ,
    3. Morineau G ,
    4. Dupont C ,
    5. Coulombel I ,
    6. Vincent JP ,
    7. Nicolis I ,
    8. Benazeth S ,
    9. Cynober L and
    10. Aussel C
    : Geriatric Nutritional Risk Index: a new index for evaluating at-risk elderly medical patients. Am J Clin Nutr 82(4): 777-783, 2005. PMID: 16210706. DOI: 10.1093/ajcn/82.4.777
    OpenUrlAbstract/FREE Full Text
  3. ↵
    2. Sasaki M ,
    3. Miyoshi N ,
    4. Fujino S ,
    5. Ogino T ,
    6. Takahashi H ,
    7. Uemura M ,
    8. Matsuda C ,
    9. Yamamoto H ,
    10. Mizushima T ,
    11. Mori M and
    12. Doki Y
    : The Geriatric Nutritional Risk Index predicts postoperative complications and prognosis in elderly patients with colorectal cancer after curative surgery. Sci Rep 10(1): 10744, 2020. PMID: 32612136. DOI: 10.1038/s41598-020-67285-y
    OpenUrlCrossRefPubMed
  4. ↵
    2. Mizuno K ,
    3. Nakazato T ,
    4. Ito C ,
    5. Fujita Y ,
    6. Ogura S ,
    7. Kamiya T ,
    8. Sakurai A ,
    9. Aisa Y and
    10. Mori T
    : The prognostic value of geriatric nutritional risk index in patients with follicular lymphoma. Ann Hematol 98(7): 1777-1779, 2019. PMID: 31041513. DOI: 10.1007/s00277-019-03703-0
    OpenUrlCrossRefPubMed
    2. Kanemasa Y ,
    3. Shimoyama T ,
    4. Sasaki Y ,
    5. Hishima T and
    6. Omuro Y
    : Geriatric nutritional risk index as a prognostic factor in patients with diffuse large B cell lymphoma. Ann Hematol 97(6): 999-1007, 2018. PMID: 29427185. DOI: 10.1007/s00277-018-3273-1
    OpenUrlCrossRefPubMed
  6. ↵
    2. Miyake H ,
    3. Tei H and
    4. Fujisawa M
    : Geriatric Nutrition Risk Index is an important predictor of cancer-specific survival, but not recurrence-free survival, in patients undergoing surgical resection for non-metastatic renal cell carcinoma. Curr Urol 10(1): 26-31, 2017. PMID: 28559774. DOI: 10.1159/000447147
    OpenUrlCrossRefPubMed
  7. ↵
    2. Brierley JD ,
    3. Gospodarowicz MK and
    4. Wittekind C
    : TNM classification of malignant tumours, eighth edition. Wiley-Blackwell, pp. 73-77, 2017.
  8. ↵
    2. Duraes LC ,
    3. Stocchi L ,
    4. Steele SR ,
    5. Kalady MF ,
    6. Church JM ,
    7. Gorgun E ,
    8. Liska D ,
    9. Kessler H ,
    10. Lavryk OA and
    11. Delaney CP
    : The relationship between Clavien-Dindo morbidity classification and oncologic outcomes after colorectal cancer resection. Ann Surg Oncol 25(1): 188-196, 2018. PMID: 29116488. DOI: 10.1245/s10434-017-6142-6
    OpenUrlCrossRefPubMed
  9. ↵
    2. Iseki Y ,
    3. Shibutani M ,
    4. Maeda K ,
    5. Nagahara H ,
    6. Ohtani H ,
    7. Sugano K ,
    8. Ikeya T ,
    9. Muguruma K ,
    10. Tanaka H ,
    11. Toyokawa T ,
    12. Sakurai K and
    13. Hirakawa K
    : Impact of the preoperative controlling nutritional status (CONUT) score on the survival after curative surgery for colorectal cancer. PLoS One 10(7): e0132488, 2015. PMID: 26147805. DOI: 10.1371/journal.pone.0132488
    OpenUrlCrossRefPubMed
  10. ↵
    2. Schwegler I ,
    3. von Holzen A ,
    4. Gutzwiller JP ,
    5. Schlumpf R ,
    6. Mühlebach S and
    7. Stanga Z
    : Nutritional risk is a clinical predictor of postoperative mortality and morbidity in surgery for colorectal cancer. Br J Surg 97(1): 92-97, 2010. PMID: 20013933. DOI: 10.1002/bjs.6805
    OpenUrlCrossRefPubMed
  11. ↵
    2. Kanda M ,
    3. Fujii T ,
    4. Kodera Y ,
    5. Nagai S ,
    6. Takeda S and
    7. Nakao A
    : Nutritional predictors of postoperative outcome in pancreatic cancer. Br J Surg 98(2): 268-274, 2011. PMID: 20960457. DOI: 10.1002/bjs.7305
    OpenUrlCrossRefPubMed
  12. ↵
    2. Zhang Y ,
    3. Zhu JY ,
    4. Zhou LN ,
    5. Tang M ,
    6. Chen MB and
    7. Tao M
    : Predicting the prognosis of gastric cancer by albumin/globulin ratio and the Prognostic Nutritional Index. Nutr Cancer 72(4): 635-644, 2020. PMID: 31423840. DOI: 10.1080/01635581.2019.1651347
    OpenUrlCrossRefPubMed
    2. Numata K ,
    3. Ono Y ,
    4. Toda S ,
    5. Kamioka Y ,
    6. Suematsu H ,
    7. Sawazaki S ,
    8. Tsuchida K ,
    9. Higuchi A ,
    10. Saeki H ,
    11. Rino Y ,
    12. Masuda M and
    13. Matsukawa H
    : Modified Glasgow Prognostic Score and carcinoembryonic antigen predict poor prognosis in elderly patients with colorectal cancer. Oncol Res Treat 43(4): 125-133, 2020. PMID: 32040953. DOI: 10.1159/000505930
    OpenUrlCrossRefPubMed
    2. Chen JH ,
    3. Zhai ET ,
    4. Yuan YJ ,
    5. Wu KM ,
    6. Xu JB ,
    7. Peng JJ ,
    8. Chen CQ ,
    9. He YL and
    10. Cai SR
    : Systemic immune-inflammation index for predicting prognosis of colorectal cancer. World J Gastroenterol 23(34): 6261-6272, 2017. PMID: 28974892. DOI: 10.3748/wjg.v23.i34.6261
    OpenUrlCrossRefPubMed
  15. ↵
    2. Hirahara T ,
    3. Arigami T ,
    4. Yanagita S ,
    5. Matsushita D ,
    6. Uchikado Y ,
    7. Kita Y ,
    8. Mori S ,
    9. Sasaki K ,
    10. Omoto I ,
    11. Kurahara H ,
    12. Maemura K ,
    13. Okubo K ,
    14. Uenosono Y ,
    15. Ishigami S and
    16. Natsugoe S
    : Combined neutrophil-lymphocyte ratio and platelet-lymphocyte ratio predicts chemotherapy response and prognosis in patients with advanced gastric cancer. BMC Cancer 19(1): 672, 2019. PMID: 31286873. DOI: 10.1186/s12885-019-5903-y
    OpenUrlCrossRefPubMed
  16. ↵
    2. Buzby GP ,
    3. Williford WO ,
    4. Peterson OL ,
    5. Crosby LO ,
    6. Page CP ,
    7. Reinhardt GF and
    8. Mullen JL
    : A randomized clinical trial of total parenteral nutrition in malnourished surgical patients: the rationale and impact of previous clinical trials and pilot study on protocol design. Am J Clin Nutr 47(2 Suppl): 357-365, 1988. PMID: 3124597. DOI: 10.1093/ajcn/47.2.357
    OpenUrlAbstract/FREE Full Text
  17. ↵
    2. Buzby GP ,
    3. Knox LS ,
    4. Crosby LO ,
    5. Eisenberg JM ,
    6. Haakenson CM ,
    7. McNeal GE ,
    8. Page CP ,
    9. Peterson OL ,
    10. Reinhardt GF and
    11. Williford WO
    : Study protocol: a randomized clinical trial of total parenteral nutrition in malnourished surgical patients. Am J Clin Nutr 47(2 Suppl): 366-381, 1988. PMID: 3124598. DOI: 10.1093/ajcn/47.2.366
    OpenUrlAbstract/FREE Full Text
  18. ↵
    2. Robbins LJ
    : Evaluation of weight loss in the elderly. Geriatrics 44(4): 31-4, 37, 1989. PMID: 2647586.
    OpenUrlPubMed
  19. ↵
    2. Adachi T ,
    3. Hinoi T ,
    4. Kinugawa Y ,
    5. Enomoto T ,
    6. Maruyama S ,
    7. Hirose H ,
    8. Naito M ,
    9. Tanaka K ,
    10. Miyake Y and
    11. Watanabe M
    : Lower body mass index predicts worse cancer-specific prognosis in octogenarians with colorectal cancer. J Gastroenterol 51(8): 779-787, 2016. PMID: 26660524. DOI: 10.1007/s00535-015-1147-z
    OpenUrlCrossRefPubMed
    2. Shibutani M ,
    3. Maeda K ,
    4. Nagahara H ,
    5. Ohtani H ,
    6. Iseki Y ,
    7. Ikeya T ,
    8. Sugano K and
    9. Hirakawa K
    : The prognostic significance of the postoperative prognostic nutritional index in patients with colorectal cancer. BMC Cancer 15: 521, 2015. PMID: 26177820. DOI: 10.1186/s12885-015-1537-x
    OpenUrlCrossRefPubMed
    2. Reisinger KW ,
    3. Bosmans JW ,
    4. Uittenbogaart M ,
    5. Alsoumali A ,
    6. Poeze M ,
    7. Sosef MN and
    8. Derikx JP
    : Loss of skeletal muscle mass during neoadjuvant chemoradiotherapy predicts postoperative mortality in esophageal cancer surgery. Ann Surg Oncol 22(13): 4445-4452, 2015. PMID: 25893413. DOI: 10.1245/s10434-015-4558-4
    OpenUrlCrossRefPubMed
  22. ↵
    2. Gupta D ,
    3. Lammersfeld CA ,
    4. Vashi PG ,
    5. Burrows J ,
    6. Lis CG and
    7. Grutsch JF
    : Prognostic significance of Subjective Global Assessment (SGA) in advanced colorectal cancer. Eur J Clin Nutr 59(1): 35-40, 2005. PMID: 15252422. DOI: 10.1038/sj.ejcn.16020293765
    OpenUrlCrossRefPubMed
  23. ↵
    2. Tan BH ,
    3. Birdsell LA ,
    4. Martin L ,
    5. Baracos VE and
    6. Fearon KC
    : Sarcopenia in an overweight or obese patient is an adverse prognostic factor in pancreatic cancer. Clin Cancer Res 15(22): 6973-6979, 2009. PMID: 19887488. DOI: 10.1158/1078-0432.CCR-09-1525
    OpenUrlAbstract/FREE Full Text
    2. Harimoto N ,
    3. Shirabe K ,
    4. Yamashita YI ,
    5. Ikegami T ,
    6. Yoshizumi T ,
    7. Soejima Y ,
    8. Ikeda T ,
    9. Maehara Y ,
    10. Nishie A and
    11. Yamanaka T
    : Sarcopenia as a predictor of prognosis in patients following hepatectomy for hepatocellular carcinoma. Br J Surg 100(11): 1523-1530, 2013. PMID: 24037576. DOI: 10.1002/bjs.9258
    OpenUrlCrossRefPubMed
  25. ↵
    2. Baracos V and
    3. Kazemi-Bajestani SM
    : Clinical outcomes related to muscle mass in humans with cancer and catabolic illnesses. Int J Biochem Cell Biol 45(10): 2302-2308, 2013. PMID: 23819995. DOI: 10.1016/j.biocel.2013.06.016
    OpenUrlCrossRefPubMed
  26. ↵
    2. Shoji F ,
    3. Matsubara T ,
    4. Kozuma Y ,
    5. Haratake N ,
    6. Akamine T ,
    7. Takamori S ,
    8. Katsura M ,
    9. Toyokawa G ,
    10. Okamoto T and
    11. Maehara Y
    : Relationship between preoperative sarcopenia status and immuno-nutritional parameters in patients with early-stage nonsmall cell lung cancer. Anticancer Res 37(12): 6997-7003, 2017. PMID: 29187486. DOI: 10.21873/anticanres.12168
    OpenUrlAbstract/FREE Full Text
  27. ↵
    2. Cereda E and
    3. Vanotti A
    : The new Geriatric Nutritional Risk Index is a good predictor of muscle dysfunction in institutionalized older patients. Clin Nutr 26(1): 78-83, 2007. PMID: 17067726. DOI: 10.1016/j.clnu.2006.09.007
    OpenUrlCrossRefPubMed
  28. ↵
    2. Kaneko H ,
    3. Suzuki S ,
    4. Goto M ,
    5. Yuzawa Y ,
    6. Arita T ,
    7. Yagi N ,
    8. Murata N ,
    9. Kato Y ,
    10. Kano H ,
    11. Matsuno S ,
    12. Otsuka T ,
    13. Uejima T ,
    14. Takai H ,
    15. Oikawa Y ,
    16. Kunihara T ,
    17. Nagashima K ,
    18. Kirigaya H ,
    19. Sagara K ,
    20. Sawada H ,
    21. Aizawa T ,
    22. Yajima J and
    23. Yamashita T
    : Geriatric nutritional risk index in hospitalized heart failure patients. Int J Cardiol 181: 213-215, 2015. PMID: 25528314. DOI: 10.1016/j.ijcard.2014.11.167
    OpenUrlCrossRefPubMed
  29. ↵
    2. Komatsu M ,
    3. Okazaki M ,
    4. Tsuchiya K ,
    5. Kawaguchi H and
    6. Nitta K
    : Geriatric Nutritional Risk Index is a simple predictor of mortality in chronic hemodialysis patients. Blood Purif 39(4): 281-287, 2015. PMID: 25925239. DOI: 10.1159/000381798
    OpenUrlCrossRefPubMed
  30. ↵
    2. Matsumura T ,
    3. Mitani Y ,
    4. Oki Y ,
    5. Fujimoto Y ,
    6. Ohira M ,
    7. Kaneko H ,
    8. Kawashima T ,
    9. Nishio M and
    10. Ishikawa A
    : Comparison of Geriatric Nutritional Risk Index scores on physical performance among elderly patients with chronic obstructive pulmonary disease. Heart Lung 44(6): 534-538, 2015. PMID: 26409897. DOI: 10.1016/j.hrtlng.2015.08.004
    OpenUrlCrossRefPubMed
  31. ↵
    2. Li L ,
    3. Wang H ,
    4. Yang J ,
    5. Jiang L ,
    6. Yang J ,
    7. Wu H ,
    8. Wen T and
    9. Yan L
    : Geriatric nutritional risk index predicts prognosis after hepatectomy in elderly patients with hepatitis B virus-related hepatocellular carcinoma. Sci Rep 8(1): 12561, 2018. PMID: 30135506. DOI: 10.1038/s41598-018-30906-8
    OpenUrlCrossRefPubMed
  32. ↵
    2. Kushiyama S ,
    3. Sakurai K ,
    4. Kubo N ,
    5. Tamamori Y ,
    6. Nishii T ,
    7. Tachimori A ,
    8. Inoue T and
    9. Maeda K
    : The preoperative Geriatric Nutritional Risk Index predicts postoperative complications in elderly patients with gastric cancer undergoing gastrectomy. In Vivo 32(6): 1667-1672, 2018. PMID: 30348732. DOI: 10.21873/invivo.11430
    OpenUrlAbstract/FREE Full Text
  33. ↵
    2. Bo Y ,
    3. Wang K ,
    4. Liu Y ,
    5. You J ,
    6. Cui H ,
    7. Zhu Y ,
    8. Lu Q and
    9. Yuan L
    : The Geriatric Nutritional Risk Index predicts survival in elderly esophageal squamous cell carcinoma patients with radiotherapy. PLoS One 11(5): e0155903, 2016. PMID: 27196126. DOI: 10.1371/j ournal .pone.0155903
    OpenUrlCrossRefPubMed
  34. ↵
    2. Iguchi T ,
    3. Sugimachi K ,
    4. Mano Y ,
    5. Motomura T ,
    6. Sugiyama M ,
    7. Ota M ,
    8. Ikebe M ,
    9. Esaki T ,
    10. Yoshizumi T ,
    11. Morita M ,
    12. Mori M and
    13. Toh Y
    : Prognostic Impact of Geriatric Nutritional Risk Index in patients with synchronous colorectal liver metastasis. Anticancer Res 40(7): 4165-4171, 2020. PMID: 32620666. DOI: 10.21873/anticanres.14416
    OpenUrlAbstract/FREE Full Text
  35. ↵
    2. Cereda E ,
    3. Pusani C ,
    4. Limonta D and
    5. Vanotti A
    : The ability of the Geriatric Nutritional Risk Index to assess the nutritional status and predict the outcome of home-care resident elderly: a comparison with the Mini Nutritional Assessment. Br J Nutr 102(4): 563-570, 2009. PMID: 19203422. DOI: 10.1017/S0007114509222677
    OpenUrlCrossRefPubMed
  36. ↵
    2. Cereda E ,
    3. Klersy C ,
    4. Pedrolli C ,
    5. Cameletti B ,
    6. Bonardi C ,
    7. Quarleri L ,
    8. Cappello S ,
    9. Bonoldi A ,
    10. Bonadeo E and
    11. Caccialanza R
    : The Geriatric Nutritional Risk Index predicts hospital length of stay and in-hospital weight loss in elderly patients. Clin Nutr 34(1): 74-78, 2015. PMID: 24508351. DOI: 10.1016/j.clnu.2014.01.017
    OpenUrlCrossRefPubMed
  37. ↵
    2. de Ulíbarri Pérez JI ,
    3. Fernández G ,
    4. Rodríguez Salvanés F and
    5. Díaz López AM
    : Nutritional screening; control of clinical undernutrition with analytical parameters. Nutr Hosp 29(4): 797-811, 2014. PMID: 24679020. DOI: 10.3305/nh.2014.29.4.7275
    OpenUrlCrossRefPubMed
  38. ↵
    2. Gupta D and
    3. Lis CG
    : Pretreatment serum albumin as a predictor of cancer survival: a systematic review of the epidemiological literature. Nutr J 9: 69, 2010. PMID: 21176210. DOI: 10.1186/1475-2891-9-69
    OpenUrlCrossRefPubMed
  39. ↵
    2. Saunders J and
    3. Smith T
    : Malnutrition: causes and consequences. Clin Med (Lond) 10(6): 624-627, 2010. PMID: 21413492. DOI: 10.7861/clinmedicine.10-6-624
    OpenUrlFREE Full Text
  40. ↵
    2. Pae M ,
    3. Meydani SN and
    4. Wu D
    : The role of nutrition in enhancing immunity in aging. Aging Dis 3(1): 91-129, 2012. PMID: 22500273.
    OpenUrlPubMed
  41. ↵
    2. Lesourd B and
    3. Mazari L
    : Nutrition and immunity in the elderly. Proc Nutr Soc 58(3): 685-695, 1999. PMID: 10604204. DOI: 10.1017/s0029665199000907
    OpenUrlCrossRefPubMed
  42. ↵
    2. Mazur G ,
    3. Bogunia-Kubik K ,
    4. Wrobel T ,
    5. Kuliczkowski K and
    6. Lange A
    : TGF-beta1 gene polymorphisms influence the course of the disease in non-Hodgkin’s lymphoma patients. Cytokine 33(3): 145-149, 2006. PMID: 16524740. DOI: 10.1016/j.cyto.2005.12.010
    OpenUrlCrossRefPubMed
  43. ↵
    2. Ray-Coquard I ,
    3. Cropet C ,
    4. Van Glabbeke M ,
    5. Sebban C ,
    6. Le Cesne A ,
    7. Judson I ,
    8. Tredan O ,
    9. Verweij J ,
    10. Biron P ,
    11. Labidi I ,
    12. Guastalla JP ,
    13. Bachelot T ,
    14. Perol D ,
    15. Chabaud S ,
    16. Hogendoorn PC ,
    17. Cassier P ,
    18. Dufresne A ,
    19. Blay JY and European Organization for Research and Treatment of Cancer Soft Tissue and Bone Sarcoma Group
    : Lymphopenia as a prognostic factor for overall survival in advanced carcinomas, sarcomas, and lymphomas. Cancer Res 69(13): 5383-5391, 2009. PMID: 19549917. DOI: 10.1158/0008-5472.CAN-08-3845
    OpenUrlAbstract/FREE Full Text
  44. ↵
    2. Diakos CI ,
    3. Charles KA ,
    4. McMillan DC and
    5. Clarke SJ
    : Cancer-related inflammation and treatment effectiveness. Lancet Oncol 15(11): e493-e503, 2014. PMID: 25281468. DOI: 10.1016/S1470-2045(14)70263-3
    OpenUrlCrossRefPubMed
  45. ↵
    2. Fried LP ,
    3. Tangen CM ,
    4. Walston J ,
    5. Newman AB ,
    6. Hirsch C ,
    7. Gottdiener J ,
    8. Seeman T ,
    9. Tracy R ,
    10. Kop WJ ,
    11. Burke G ,
    12. McBurnie MA and Cardiovascular Health Study Collaborative Research Group
    : Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 56(3): M146-M156, 2001. PMID: 11253156. DOI: 10.1093/gerona/56.3.m146
    OpenUrlCrossRefPubMed
Back to top

In this issue

Print
Download PDF
Article Alerts
Email Article
Citation Tools
Reprints and Permissions
The Geriatric Nutritional Risk Index as a Prognosis Predictor in Patients With Rectal Cancer Receiving Neoadjuvant Chemotherapy
SOICHIRO MINAMI, NORIKATSU MIYOSHI, SHIKI FUJINO, SHINYA KATO, YUKI SEKIDO, TSUYOSHI HATA, TAKAYUKI OGINO, HIDEKAZU TAKAHASHI, MAMORU UEMURA, HIROFUMI YAMAMOTO, YUICHIRO DOKI, HIDETOSHI EGUCHI
Anticancer Research Jul 2022, 42 (7) 3759-3766; DOI: 10.21873/anticanres.15866
Twitter logo Facebook logo Mendeley logo

Jump to section

Keywords