Indian Journal of Palliative Care
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 »  Abstract
 » Introduction
 » Patients and Methods
 » Results
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Table of Contents 
ORIGINAL ARTICLE
Year : 2020  |  Volume : 26  |  Issue : 4  |  Page : 433-436

Impact of prognostic nutritional index on terminal cancer patients


1 Department of Medical Oncology, Faculty of Medicine, Zagazig University, Zagazig, Egypt; Oncology Center, King Salman Armed Forces Hospital, Tabuk, KSA
2 Oncology Center, King Salman Armed Forces Hospital, Tabuk, KSA
3 Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, Suez Canal University, Egypt

Date of Submission23-Jan-2020
Date of Acceptance26-Mar-2020
Date of Web Publication19-Nov-2020

Correspondence Address:
Amrallah A Mohammed
29, Saad Zaghloul, Postal Code 44519, Egypt.

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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/IJPC.IJPC_18_20

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 » Abstract 


Background: In terminal cancer patients (TCPs), one of the most important things is to define the survival to help the main responsible physicians, patients, and main caregivers make decisions, set goals, and work across the end-of-life strategies. Patients and Methods: We retrospectively reviewed the medical files of TCPs, who died during September 2011 and December 2017, to recognize the correlation between prognostic nutritional indices (PNIs) and survival in those subtypes of patients. The receiver operating characteristic (ROC) curve was used to identify the cutoff value of PNI. Results: A total of 858 TCPs were eligible and included, the median age was 62 years (range: 18–107). The most common primary cancer sites were colorectal cancer in 151 patients (17.6%), hepatobiliary in 129 (15%), lung cancer in 115 (13.4%), breast cancer in 114 (13.3%), and genitourinary in 80 (9.3%). The mean value of PNI for all cancer types was 32.9 ± 6.7. The values showed different levels across cancer types. For patients who lived >2 weeks, PNI was 36.7 compared with that who died within 2 weeks was 29.3, which was a statistically significant (P < 0.001). By the ROC curve, the cutoff value of PNI was 32.3 and area under the curve was 0.888. The sensitivity, specificity, positive predictive value, and negative predictive value were 91.28% (95% confidence interval [CI]: 88.2–93.8), 71.09% (95% CI: 66.5–75.4), 76.5% (95% CI: 73.7–79.2), and 88.8% (95% CI: 85.3–91.5), respectively. Conclusion: The PNI is an easy and an applicable biomarker to estimate life expectancy in TCPs.


Keywords: Life expectancy, prognostic nutritional index, terminal cancer


How to cite this article:
Mohammed AA, Al-Zahrani O, Elsayed FM. Impact of prognostic nutritional index on terminal cancer patients. Indian J Palliat Care 2020;26:433-6

How to cite this URL:
Mohammed AA, Al-Zahrani O, Elsayed FM. Impact of prognostic nutritional index on terminal cancer patients. Indian J Palliat Care [serial online] 2020 [cited 2020 Dec 5];26:433-6. Available from: https://www.jpalliativecare.com/text.asp?2020/26/4/433/300792





 » Introduction Top


Nevertheless, some oncologists prescribe anticancer therapy to terminal cancer patients (TCPs) aiming to extend survival, all the same, it is not always a suitable option.[1]

Terminal cancer, also called end-stage cancer, means cancer beyond the cure. While advanced cancer may respond to therapy, terminal cancer usually has no response. Thus, the main rationales in the treatment focus on improving the quality of life and making them more comfortable.[2]

In general, oncologists and palliative care teams depend on clinical factors and nutritional status to determine life expectancy. While the Karnofsky Performance Status, Palliative Prognostic Score (PPS), and Palliative Prognostic Index (PPI) represent the main points used to define life expectancy, they are based on subjective factors affecting their accuracy.[3]

The prognostic nutritional index (PNI) was initially suggested to evaluate the nutritional status in the gastrointestinal operations included malignant tumors in the perioperative setting.[4]

The PNI is based on laboratory indicators which can be simply achieved from routine blood tests. It is calculated as 10 × serum albumin (g/dl) + 0.005 × lymphocyte count.[5]

Seeing the TCPs, a systemic review included eight evaluable published studies, provided ≥1500 predictions survival. The authors had proved that the main responsible physicians (MRPs) usually overestimate the survival in those patients.[6] Thus far, the utilization of PNI as a marker of disease behavior is not fully investigated in those subtypes of patients.

Consequently, the aim in this work is to yield a realistic estimate about the value of the PNI in life expectancy to help the MRPs, patients, and main caregivers make decisions, set goals, and work across the end-of-life (EOL) strategies.


 » Patients and Methods Top


The current retrospective study included 858 TCPs with terminal cancer between September 2011 and December 2017 who died in the Medical Oncology Department, Zagazig University, Egypt, and King Abdullah Medical City in Saudi Arabia. The eligibility criteria included aged ≥18 years old, histopathological confirmed cancer, and the evidence of advanced disease. Patients with hematological malignancy, treatment with adjuvant or curative intent were excluded from the study. Clinicopathological data included primary site, age, sex, complete blood count, and liver function were collected from patients' files and the electronic system.

PNI was calculated as 10 × the serum albumin concentration (g/dL) + 0.005 × the total lymphocyte count (per mm3), at the last admission before death.

Statistical methods

All statistics were done using the Statistical Package for the Social Sciences 20.0 for Windows (SPSS Inc., Chicago, IL, USA). P < 0.05 was considered statistically significant.


 » Results Top


A total of 858 TCPs with a median age of62 years (mean age: 60.8 ± 15.5 years) were included in the study. The most common primary sites of cancers were colorectal cancer in 151 patients, hepatobiliary in 129, lung cancer in 115, breast cancer in 114, genitourinary in 80, pancreatic cancer in 49, head-and-neck cancer in 45, gastric cancer in 43, and prostatic cancer in 22.

After a median follow-up of 14 days (range from 0 to 176 days), 49.2% of patients survived ≥2 weeks. The patients' features are illustrated in [Table 1].
Table 1: The main patients' features (n=858)

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The mean value of PNI for all types of cancer was 32.9 ± 6.7 at the time of admission. The values showed different levels across cancer types.

For patients who lived >2 weeks, PNI was 36.7 compared with that who died within 2 weeks was 29.3, which was a statistically significant (P< 0.001). [Table 2] revealed the PNI distribution through the included patients.
Table 2: Prognostic nutritional index distribution through the included patients

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By the receiver operating characteristic curve, the cutoff value of PNI was 32.3, according to the Youden index, area under the curve (AUC) was 0.888 [Figure 1]. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 91.28% (95% confidence interval [CI]: 88.2–93.8), 71.09% (95% CI: 66.5–75.4), 76.5% (95% CI: 73.7–79.2), and 88.8% (95% CI: 85.3–91.5), respectively [Table 3].
Figure 1: Receiver operating characteristic analysis of prognostic nutritional index

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Table 3: Sensitivity and specificity with prognostic nutritional index cutoff value of 32.3

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 » Discussion Top


In the current study, the AUC of PNI was 0.888, with a sensitivity of 91.28%, specificity of 71.09%, PPV of 76.5%, and NPV of 88.8%. This finding did not match with a previous study done by Nakamura et al. who showed that the sensitivity, specificity, PPV, and NPV were 74.8%, 62.2%, 68.1%, and 69.6%, respectively.[3] This deviation between the two studies may be referred to differences in sample size and primary cancer sites (in Nakamura et al. study, 278 patients and approximately half of the patients had colorectal and gastric cancers).

In other studies, the results were ranged from 0.648% to 0.732%, 59.6% to 82.3%, and 57.9% to 65.3% for the AUC, sensitivity, and specificity, retrospectively. However, the patients in these studies were not with terminal cancer.[7],[8],[9],[10],[11],[12],[13],[14],[15]

Notably, in the present study, we observed that patients with high PNI level experienced better survival compared with those with low PNI (patients lived >2 weeks, PNI was 36.7 compared with that who died within 2 weeks was 29.3, which was a statistically significant; P < 0.001).

This significant observation is matched with that presented previously with Nakamura et al., Abe et al., and Koyama et al.[3],[16],[17]

A systematically structured review involved 30 articles demonstrated that lymphocyte count and serum albumin are grade A evidence in estimating the life expectancy in TCPs.[18]

The survival estimation is a decisive factor for MRPs and patients in any grave illness. In TCPs, the increased significance as the goal of handling may be shifted from cancer-directed therapy to palliative care. Despite the magnitude of life expectancy in that subgroup of patients, it is almost always imperfect.[19]

The oncologists usually estimate the survival based on their clinical experience and anticipation. It is constantly optimistic and incorrect. They believed that patients should live more than they really do. A systemic review included 12 articles on clinical predictions of survival (CPS), and 19 prognostic factors reported that the clinical prediction alone is weak and incorrect.[20]

A prospective study included 343 physicians to estimate their prognostic accuracy for 468 patients with terminal illness at the hospice referral in Chicago. Only20% of physicians were accurate, and the survival overestimated by a 5.3 factor.[21]

Furthermore, through a multicenter prospective study carried out in 58, the Japanese palliative care centers involved 2036 patients to assess the accuracy of CPS and evaluate its relationship with actual survival in patients with advanced cancer into four groups (home health-care palliative team, hospital palliative teams, palliative care units, and also those receiving chemotherapy). The CPS was 35% (95%: CI 33%–37%), the pessimistic CPS was 20% (95% CI: 18%–22%), and the optimistic CPS was 45% (95% CI: 43%–47%), in the whole sample.[22]

Moreover, Gripp et al. conducted a prospective study on 216 patients to assess the life expectancy showed that physicians' survival estimates were uncertain, mostly in patients about death.[23]

In addition, numerous studies had reported that many TCPs continue to receive anticancer therapy they may not need it and even associated with both bad qualities of life and poor outcomes.[1],[24],[25],[26],[27] This is possibly due to a deficiency of an easy, accurate, and applicable tools for a more rigorous identification of the life expectancy in that subtype of patients.

At the EOL, patients would not prefer chemotherapy if they recognized that they held a poor prognosis. To overcome these drawbacks and improve the accuracy of the prognostication, the investigators tried to develop an index based mainly on simple laboratory tests.

PNI is different from other indices used in estimation of life expectancy as KPS, PPS, and PPI. Being based on an objective data, it can be easily incorporated into a computerized system as well as the possibility of use as common screening index with vital signs in TCPs.

Limitations

The retrospective studies are most always accused of bias, as the data depend on the file documentations. The study did not include all types of cancers. Moreover, most of the patients used corticosteroids, as they have significances in the palliative treatment. Furthermore, the steroid hormone can induce apoptosis in lymphocytes, so PNI may be changed by the steroid effect.


 » Conclusion Top


The PNI is an easy and an applicable biomarker and can be added to routine evaluation with vital signs to estimate life expectancy in TCPs.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
 » References Top

1.
Mohammed A, Al-Zahrani O, Salem R, El-Sayed F. Aggressive care at the end of life; where are we? Indian J Palliat Care 2019;25:539-43.  Back to cited text no. 1
[PUBMED]  [Full text]  
2.
Kim S, Shin D, Kim S, Yang H, Nam E, Jho H, et al. Terminal versus advanced cancer: Do the general population and health care professionals share a common language? Cancer Res Treat 2016;48:759-67.  Back to cited text no. 2
    
3.
Nakamura Y, Nagao J, Saida Y, Watanabe M, Okamoto Y, Koji Asai K, et al. Use of the prognostic nutritional index to predict clinical outcomes of patients with terminal stage cancer. Palliat Care Res 2013;8:199-202.  Back to cited text no. 3
    
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Onodera T, Goseki N, Kosaki G. Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients. Nihon Geka Gakkai Zasshi 1984;85:1001-5.  Back to cited text no. 5
    
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Glare P, Virik K, Jones M, Hudson M, Eychmuller S, Simes J, et al. A systematic review of physicians' survival predictions in terminally ill cancer patients. BMJ 2003;327:195-8.  Back to cited text no. 6
    
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Migita K, Takayama T, Saeki K, Matsumoto S, Wakatsuki K, Enomoto K, et al. The prognostic nutritional index predicts long-term outcomes of gastric cancer patients independent of tumor stage. Ann Surg Oncol 2013;20:2647-54.  Back to cited text no. 7
    
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Tokunaga R, Sakamoto Y, Nakagawa S, Miyamoto Y, Yoshida N, Oki E, et al. Prognostic nutritional index predicts severe complications, recurrence, and poor prognosis in patients with colorectal cancer undergoing primary tumor resection. Dis Colon Rectum 2015;58:1048-57.  Back to cited text no. 8
    
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Liu X, Qiu H, Liu J, Chen S, Xu D, Li W, et al. A novel prognostic score, based on preoperative nutritional status, predicts outcomes of patients after curative resection for gastric cancer. J Cancer 2016;7:2148-56.  Back to cited text no. 9
    
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Zhao Y, Deng Y, Peng J, Sui Q, Lin J, Qiu M, et al. Does the preoperative prognostic nutritional index predict survival in patients with liver metastases from colorectal cancer who underwent curative resection? J Cancer 2018;9:2167-74.  Back to cited text no. 10
    
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Perkins NJ, Schisterman EF. The inconsistency of “optimal ”cut points obtained using two criteria based on the receiver operating characteristic curve. Am J Epidemiol 2006;163:670-5.  Back to cited text no. 11
    
12.
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Liu X, Qiu H, Zhang P, Feng X, Chen T, Li Y, et al. Prognostic role of tumor necrosis in patients undergoing curative resection for gastric gastrointestinal stromal tumor: A multicenter analysis of 740 cases in China. Cancer Med 2017;6:2796-803.  Back to cited text no. 13
    
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Zhao WY, Xu J, Wang M, Zhang ZZ, Tu L, Wang CJ, et al. Evaluation of high-risk clinicopathological indicators in gastrointestinal stromal tumors for prognosis and imatinib treatment outcome. BMC Gastroenterol 2014;14:1-8.  Back to cited text no. 14
    
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Sakurai K, Tamura T, Toyokawa T, Amano R, Kubo N, Tanaka H, et al. Low Preoperative prognostic nutritional index predicts poor survival post-gastrectomy in elderly patients with gastric cancer. Ann Surg Oncol 2016;23:3669-76.  Back to cited text no. 15
    
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Abe A, Kurita K, Hayashi H, Minagawa M. Prognostic nutritional index predicts life expectancy of patients with end-stage oral cancer: A retrospective study. Surg Sci 2018;9:487-95.  Back to cited text no. 16
    
17.
Koyama N, Matsumura C, Morii H, Hasegawa C, Hira D, Daigo Y, et al. Investigation of optimal time for starting betamethasone using fatigue scores and prognostic nutritional index in terminally ill patients with cancer-related fatigue. Am J Hosp Palliat Care 2017;34:449-55.  Back to cited text no. 17
    
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Reid VL, McDonald R, Nwosu AC, Mason SR, Probert C, Ellershaw JE, et al. A systematically structured review of biomarkers of dying in cancer patients in the last months of life; an exploration of the biology of dying. PLoS One 2017;6:e0175123.  Back to cited text no. 18
    
19.
Lee SJ, Fairclough D, Antin JH, Weeks JC. Discrepancies between patient and physician estimates for the success of stem cell transplantation. JAMA 2001;285:1034.  Back to cited text no. 19
    
20.
Chow E, Harth T, Hruby G, Finkelstein J, Wu J, Danjoux C. How accurate are physicians' clinical predictions of survival and the available prognostic tools in estimating survival times in terminally ill cancer patients? A systematic review. Clin Oncol (R Coll Radiol) 2001;13:209.  Back to cited text no. 20
    
21.
Christakis NA, Lamont EB. Extent and determinants of error in doctors' prognoses in terminally ill patients: Prospective cohort study. BMJ 2000;320:469.  Back to cited text no. 21
    
22.
Amano K, Maeda I, Shimoyama S, Shinjo T, Shirayama H, Yamada T, et al. The accuracy of physicians' clinical predictions of survival in patients with advanced cancer. J Pain Symptom Manage 2015;50:139-46.  Back to cited text no. 22
    
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Gripp S, Moeller S, Bölke E, Schmitt G, Matuschek C, Asgari S, et al. Survival prediction in terminally ill cancer patients with clinical estimates, laboratory tests, and self-rated anxiety and depression. J Clin Oncol 2007;25:3313-20.  Back to cited text no. 23
    
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27.
Temel JS, Greer JA, Admane S, Shinjo T, Shirayama H, Yamada T, et al. Longitudinal perceptions of prognosis and goals of therapy in patients with metastatic non-small-cell lung cancer: Results of a randomized study of early palliative care. J Clin Oncol 2011;29:2319-26.  Back to cited text no. 27
    


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