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. 2022 Aug 5;17(8):e0271821. doi: 10.1371/journal.pone.0271821

Prognostic nutritional index as a prognostic factor for renal cell carcinoma: A systematic review and meta-analysis

Sung Ryul Shim 1, Sun Il Kim 2, Se Joong Kim 2, Dae Sung Cho 2,*
Editor: Giuseppe Lucarelli3
PMCID: PMC9355260  PMID: 35930538

Abstract

Background

Prognostic nutritional index (PNI) is a simple parameter which reflects patient’s nutritional and inflammatory status and reported as a prognostic factor for renal cell carcinoma (RCC). Studies were included from database inception until February 2, 2022. The aim of this study is to evaluate prognostic value of PNI by meta-analysis of the diagnostic test accuracy in RCC.

Methods and findings

Studies were retrieved from PubMed, Cochrane, and EMBASE databases and assessed sensitivity, specificity, summary receiver operating characteristic curve (SROC) and area under curve (AUC). Totally, we identified 11 studies with a total of 7,296 patients were included to evaluate the prognostic value of PNI in RCC finally. They indicated a pooled sensitivity of 0.733 (95% CI, 0.651–0.802), specificity of 0.615 (95% CI, 0.528–0.695), diagnostic odds ratio (DOR) of 4.382 (95% CI, 3.148–6.101) and AUC of 0.72 (95% CI, 0.68–0.76). Heterogeneity was significant and univariate meta-regression revealed that metastasis and cut-off value of PNI might be the potential source of heterogeneity. Multivariate meta-regression analysis also demonstrated that metastasis might be the source of heterogeneity.

Conclusions

PNI demonstrated a good diagnostic accuracy as a prognostic factor for RCC and especially in case of metastatic RCC.

Introduction

The ability to precisely predict the prognosis of patients with cancer is essential to determine the most appropriate treatment strategy and follow-up plan. Several prognostic factors for renal cell carcinoma (RCC) have been established or under estimation, including the pathologic T stage, Fuhrman nuclear grade, tumor size, lymph node metastasis, and distant metastasis [1, 2]. Recently, there has been increasing evidence that nutritional status and the host immune response to RCC can significantly affect cancer progression and survival after treatment.

The prognostic nutritional index (PNI), a novel method to assess immune and nutritional status on the basis of the serum lymphocyte count and albumin level, has been introduced as a simple tool with prognostic value for patients with RCC [3–13]. However, insufficient results have been reported regarding the utility of the PNI in patients with RCC, due to differences among studies in sample size, presence of metastasis, patient characteristics, and other factors [14]. Therefore, we performed this pooled meta-analysis to assess the diagnostic accuracy of the PNI as a prognostic factor for RCC based on available outcome data.

The aim of current study is to complete meta-analysis for diagnostic accuracy of the PNI for the prediction of survival in RCC patients, in order to provide more evidence-based data of PNI as a prognostic factor in RCC patients.

Methods

This systematic review and meta-analysis was performed in accordance with the standard Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines and was registered to the International Prospective Register of Systematic Reviews (registration no. CRD42020185171) [15].

Literature search

Based on a standardized protocol, a systemic, comprehensive search of the PubMed, Web of Science, the Cochrane Library, and EMBASE databases was conducted to identify studies that evaluated the prognostic value of the PNI in patients with RCC. Studies were included from database inception until February 2, 2022. Searches were performed using the following MeSH terms and keywords: “RCC”, “renal cancer,” “carcinoma,” “renal cell,” “kidney cancer,” “kidney neoplasms,” “clear cell carcinoma,” “adenocarcinoma, clear cell,” “non-clear cell carcinoma”, “prognostic nutritional index”, “PNI”, “prognosis”, “survival” and “outcome”. Reference lists of retrieved articles were checked to identify additional studies. Abstracts and conference proceedings were also included in the literature search.

Study selection and definition

Initial screening of search results based on titles and abstracts was performed based on structured questions using the PICO methodology; Populations: patients with RCC; Intervention: high PNI value; Comparator: low PNI value; Outcomes: survival; Decisions regarding study eligibility for inclusion in the meta-analysis, based on full-text review, were performed independently by two reviewers (SIK and DSC). Disagreements regarding data extraction and methodological assessment were resolved by discussion; remaining disagreements were resolved by a third reviewer (SJK). Each included study was carefully checked to ensure that no duplicate data were included in the meta-analysis. Studies were considered eligible for inclusion if they met the following criteria: (1) PNI values were obtained before treatment, and numbers of patients were reported according to PNI cutoff values; (2) treatments were limited to surgery, targeted therapy, or immunotherapy; and (3) the relationship between RCC prognosis and PNI value was analyzed. Papers written in languages other than English were included if the data could be extracted. Letters, review articles, and case reports were excluded. When data from the same patients were reported in more than one article, only the most recent article was included in the analysis.

The PNI was defined based on the serum albumin level and lymphocyte count using the following formula: 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count of peripheral blood (per mm3) [16].

Data extraction

The following information was extracted from the studies: (1) study attributes, including author names, year of publication, region, research period, and sample size; (2) patient characteristics, including age, sex, and follow-up duration; (3) RCC characteristics, including tumor type, stage, and distant metastasis; (4) PNI values; and (5) survival outcomes, including cancer-specific survival and/or overall survival. The absolute numbers of true-positive, true-negative, false-positive, and false-negative cases were extracted or calculated, and then incorporated into a 2 × 2 contingency table.

Statistical analysis

Pooled estimates of sensitivity and specificity and their 95% confidence intervals (CI) were calculated as the main outcome measures and were analyzed by forest plots. We used the bivariate random-effects model for analysis and pooling of the diagnostic performance measures across studies. The threshold effect was assessed using the receiver operating characteristic (ROC) plane and the Spearman correlation coefficient. The ROC plane is the graphic representation of the pairs of sensitivity and specificity, and it characteristically shows a curvilinear pattern if a threshold effect exists. Study heterogeneity was measured using the Cochran’s Q and I2 tests; p<0.10 and I2 > 50% were considered to indicate significant heterogeneity. Study heterogeneity was calculated using subgroup and meta-regression analyses were conducted to identify potential sources of heterogeneity. Publication bias was determined based on the degree of asymmetry in Deeks funnel plots. All statistical analyses were performed using Stata (version 14.0; StataCorp, College Station, TX, USA), and Meta-DiSc software (version 1.4; Meta-DiSc, Madrid, Spain). A p-value <0.05 was considered to indicate statistical significance.

Risk of bias and quality assessment

Two investigators (SIK and DSC) independently assessed all included studies for methodological quality and potential sources of bias using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool in Stata software [17]. Any disagreements regarding the appropriate category for a study were resolved by discussion.

Results

Search results and study characteristics

Fifty-three studies were identified in the initial database search. Following review of the titles and abstracts, 19 articles were identified that analyzed the relationship between RCC and the PNI. From among these 19 articles, 11 retrospective studies of 7,296 RCC patients were included in the meta-analysis [3–13]. The search strategy is presented in Fig 1. The main reasons for study exclusion were a lack of focus on the PNI when diagnosing RCC, or an absence of information regarding the PNI.

Fig 1. Flow diagram of studies identified in meta-analysis.

Fig 1

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PNI indicates Prognostic Nutritional Index.

Table 1 shows the characteristics of the eleven included studies, all of which were retrospective in nature. The studies originated from various countries, including Austria, the United States, China, Turkey, and Korea. Six studies enrolled ≥ 350 patients and five had < 350 patients. Seven studies included patients with non-metastatic RCC; the remaining four included metastatic RCC patients. Cut-off values for the PNI differed among studies.

Table 1. Characteristics of all included studies.

Study cohort Year Study region Research time Follow-up (month) M/F (n) Age (years) Tumor type Distant metastasis (n) PNI value TP FP FN TN Sensitivity (95% CI) Specificity (95% CI)
Hofbauer et al 2015 Austria and USA 1991–2012 Median: 40 892/452 (1344) Median (IQR): 62 (53–70) RCC 399 Median (IQR): 50.6 (45.8–54.6); Cut-off: 48 423 440 142 339 0.749 (0.711–0.784) 0.435 (0.400–0.471)
Broggi et al 2016 USA 2001–2014 NA 204/115 (319) Median: 61.5 Clear cell RCC 0 Mean (SD): 44.2 (6.7); Cut-off: 44.7 109 33 80 71 0.577 (0.503–0.648) 0.683 (0.584–0.771)
Jeon et al 2016 South Korea 1994–2008 Mean (range): 68.6 (1.2–212.6) 1011/426 (1437) Mean (range): 54.2 (20–85) RCC 106 Mean (range): 52.7 (27.7–85.3); Cut-off: 51 922 38 396 81 0.700 (0.674–0.724) 0.681 (0.589–0.763)
Kwon et al 2017 South Korea 2007–2014 Median (IQR): 45.3 (23.7–77.3) 99/26 (125) Median (IQR): 58 (51–66) Metastatic RCC 125 Median (IQR): 42.0 (37.2–45.1); Cut-off: 41 24 44 5 52 0.828 (0.642–0.942) 0.542 (0.437–0.644)
Kang et al 2017 South Korea 1996–2012 Mean: 79.6 241/83 (324) Median (IQR): 55 (48–64) RCC 0 Median (IQR): 45.0 (42.01–46.51); Cut-off: 45 157 6 134 27 0.540 (0.480–0.598) 0.818 (0.645–0.930)
Peng et al 2017 China 2001–2010 Median (IQR): 67 (2–108) 952/408 (1360) Median (IQR): 55 (14–87) RCC 61 NA, Cut-off: 47.625 939 39 317 65 0.748 (0.723–0.771) 0.625 (0.525–0.718)
Cai et al 2017 China 2006–2015 Median (IQR): 22 135/43 (178) Median (IQR): 60 (24–82) Metastatic RCC 178 Median (IQR): 52.3 (21.6–88.8); Cut-off: 51.62 61 37 10 70 0.859 (0.756–0.930) 0.654 (0.556–0.744)
Yasar et al 2019 Turkey 2007–2017 NA 258/138 (396) Median (IQR): 58 (29–88) Metastatic RCC 396 Median (IQR): 38.5 (18–52); Cut-off: 38.5 81 75 33 124 0.711 (0.618–0.792) 0.623 (0.552–0.691)
Cho et al 2020 South Korea 1994–2017 Median (IQR): 72 (4–272) 307/152 (459) Mean (range): 55.8 (18–81) RCC 0 Median (IQR): 53.0 (30.9–69.0); Cut-off: 51 295 0 154 10 0.657 (0.611–0.701) 1.000 (0.692–1.000)
Hu et al 2020 China 2010–2013 Median (IQR): 83 (74–93) 256/404 (660) Mean: 54.89 RCC 18 Median (IQR): 51.05 (47.9–53.88); Cut-off: 44.3 550 41 46 23 0.921 (0.901–0.942) 0.362 (0.241–0.490)
Tang et al 2021 China 2009–2014 Median (IQR): 60.9 (46.9–76.1) 442/252 (694) NA RCC 0 Cut-off: 49.075 406 21 244 23 0.622 (0.591–0.659) 0.521 (0.370–0.681)
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TP, true positive; FP, false positive; FN, false negative; TN, true negative; CI, confidence interval; NA, not applicable; RCC, renal cell carcinoma

Methodological quality assessment and risk of bias

Methodological quality assessment and risk of bias were evaluated using QUADAS-2; the results are summarized in Fig 2. Visual inspection of a Deeks’ funnel plot indicated asymmetry, i.e., significant publication bias or small-study effects (p = 0.02, S1 Fig).

Fig 2. Summary of the methodological quality of the studies evaluated by the quality assessment of diagnostic accuracy studies-2 (QUADAS-2).

Fig 2

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Quantitative synthesis

The data of the eleven studies that examined the prognostic value of the PNI for RCC were pooled. The pooled sensitivity was 0.733 (95% CI, 0.651–0.802) and the pooled specificity was 0.615 (95% CI, 0.528–0.695) (Fig 3). The diagnostic odds ratio was 4.382 (95% CI, 3.148–6.101) and the area under the curve was 0.72 (95% CI, 0.68–0.76) (Fig 4). The ROC curve to analyze the relationship between sensitivity and specificity was symmetrical, whereby the diagnostic odds ratio did not vary along the curve (p = 0.615). Furthermore, the ROC plot confirmed the absence of a threshold effect. Substantial heterogeneity among all of the included studies was observed in terms of sensitivity (Cochran’s Q = 253.64, p<0.001, I2 = 96.06%) and specificity (Cochran’s Q = 97.32, p<0.001, I2 = 89.73%).

Fig 3. Forrest plot of the sensitivity and specificity of the prognostic nutritional index as prognostic value for renal cell carcinoma.

Fig 3

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CI indicates confidence interval.

Fig 4. Summary receiver operating characteristic graph for the included studies.

Fig 4

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AUC = area under curve; SENS = sensitivity; SPEC = specificity; SROC = summary receiver operating characteristic.

Subgroup and meta-regression analyses

Subgroup analyses were performed to identify potential sources of heterogeneity in the diagnostic accuracy of the PNI among studies, including ethnicity (Asian vs. Caucasian), sample size (n ≥ 350 vs. n < 350), presence of metastasis, PNI cut-off value (≥ 50 vs. < 50), QUADAS-2 classification (low risk vs. high risk), and proportion of males (≥ 70% vs. < 70%) (Table 2). In addition, we performed subgroup analysis with American Society of Anesthesiologists (ASA) or Eastern Cooperative Oncology Group (ECOG) status. As a result of statistical analysis, there was no significant difference between ASA >2 group and ASA ≤2 group. In addtion, there were only 4 out of 11 studies showing ASA or ECOG score and limitation to the analysis. Subgroup analyses showed that presence of metastasis and PNI cut-off value affected the diagnostic accuracy of the PNI for RCC. In univariate meta-regression analysis, the sensitivity and specificity were 0.85 and 0.55, respectively, in the metastatic group, and 0.66 and 0.65, respectively, in the non-metastatic group (p = 0.01). Also, the sensitivity and specificity were 0.74 and 0.72, respectively, in the PNI ≥ 50 group, and 0.73 and 0.57, respectively, in the PNI < 50 group (p = 0.05). Multivariate meta-regression analysis demonstrated significant differences in sensitivity and specificity between the metastatic RCC and non-metastatic RCC groups (p = 0.035).

Table 2. Univariate and multivariate meta-regression analysis for identifying potential sources of heterogeneity in the diagnostic performance of screening tests.

Variable No. of studies Univariate* Multivariate†
Sensitivity Specificity p-value Diagnostic OR (95% CI) p-value
Ethnicity
 Asian 8 0.75 0.64 0.19 1.14 (0.56–2.30) 0.636
 Caucasian 3 0.68 0.58
No. of patients
 ≥350 7 0.75 0.57 0.40 0.85 (0.44–1.64) 0.522
 <350 4 0.71 0.68
Tumor type
 Metastasis 4 0.85 0.55 0.01 1.99 (1.08–3.65) 0.035
 Non-metastasis 7 0.66 0.65
PNI cut-off value
 ≥50 3 0.74 0.72 0.05 1.24 (0.61–2.54) 0.448
 <50 8 0.73 0.57
QUADAS-2
 Low risk 6 0.68 0.62 0.25 0.94 (0.38–1.47) 0.258
 High risk 5 0.79 0.60
Men, %
 ≥70 5 0.74 0.67 0.12 1.65 (0.71–3.86) 0.177
 <70 6 0.73 0.55
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PNI: Prognostic Nutritional Index, OR: odds ratio, CI: confidence interval,

*: analyzed by STATA,

†: analyzed by Meta-Disc, Univariate p-value of joint model for sensitivity and specificity

Discussion

To the best of our knowledge, this meta-analysis is the first to assess the diagnostic accuracy of the PNI as a prognostic factor for RCC. This study suggests that the PNI has value as a prognostic factor for RCC. Therefore, the PNI can aid clinicians in predicting the clinical outcomes of RCC and patients with low PNI need to be managed by nutritional support and treated in a way to correct malnutritional status. Because there was heterogeneity among the studies included in our meta-analysis, subgroup and univariate meta-regression analyses were also performed based on ethnicity, sample size, presence of metastasis, PNI cut-off values, QUADAS-2 classification, and sex ratio. These analyses showed that presence of metastasis and PNI cut-off values were potential sources of heterogeneity among the included studies. In addition, presence of metastasis (p = 0.035) were significant sources of heterogeneity in the diagnostic performance of the PNI in multivariate meta-regression analysis. These findings suggested that the PNI clearly had superior prognostic value in patients with metastatic RCC compared with non-metastatic RCC. Thus, it will be important to determine the utility of new prognostic scoring systems for patients with RCC based on the PNI, especially in case of metastatic RCC.

Several prognostic factors and models have been proposed to predict the clinical outcomes of RCC, including the tumor-node-metastasis (TNM) staging system and the Fuhrman nuclear grade. However, patients with the same TNM stage or Fuhrman grade may have significantly different prognostic courses [18]. Therefore, many studies have attempted to identify additional factors that can precisely predict the prognosis of RCC. The PNI was first used by Onodera et al. [16] to evaluate the inflammation and nutritional status of patients who underwent gastrointestinal surgery; this simple index is calculated from the serum albumin level and lymphocyte count. Because laboratory assessments, including the serum albumin level and lymphocyte count, are routinely performed before treatment of patients with RCC, PNI values can be easily measured. As reported previously [11], we observed a strong inverse relationship between the PNI and tumor aggressiveness, and a lower PNI was also associated with poorer patient outcomes. This suggests the potential for a significant association among the PNI, pathological characteristics of RCC, and other known risk factors for RCC. Additional studies are needed to more clearly elucidate how the PNI is related to the prognosis of patients with RCC.

Recently, prognostic role of circulating biomarkers associated with different features of RCC biology has been proposed, including carbonic anhydrase IX (CAIX), hypoxia-inducible factor-1α (HIF1α), CA15-3, PTX3, and C-reactive protein (CRP) [19–22]. These biomarkers are suggested to be related to the prognosis of RCC. In addition, RCC is a metabolic disease characterized by a reprogramming of energetic metabolism. In particular the metabolic flux through glycolysis is partitioned and mitochondrial bioenergetics and OxPhox are impaired, as well as lipid metabolism [23–27]. A recent study also delineated a lipidomic profile of human clear cell RCC and integrated it with transcriptomic data to connect the variations in cancer lipid metabolism with gene expression changes [28].

This meta-analysis had several limitations. First, it included relatively few studies (N = 11). Therefore, validation of the results is needed via meta-analyses including more studies. Furthermore, this meta-analysis obviously could not consider unpublished data. Second, there was considerable heterogeneity in the pooled estimates; despite attempts to determine the sources of heterogeneity through meta-regression, a substantial proportion of the variance remained unexplained, and many factors could not be assessed because they were not reported in all of the studies. Furthermore, the small number of included studies limited the statistical power of the multivariate meta-regression. Third, individual patient characteristics (e.g., comorbidities, alcohol consumption, smoking history, and obesity) were not considered, although these may affect the PNI by inducing systemic inflammation or altering nutritional status. Fourth, randomized controlled trial and high-level studies were not included in this study and that undermined the value of this study. In conclusion, the results of this study demonstrate that diagnostic accuracy of the PNI as a prognostic factor for patients with RCC, especially metastatic RCC. In addition, the PNI is a simple, cost-effective, and widely available tool. Therefore, new prognostic scoring systems that include the PNI could be useful for predicting the prognosis of patients with RCC.

Supporting information

S1 Fig. Deeks’ funnel plot for asymmetry test for detecting publication bias.

(TIF)

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S1 File

(XLSX)

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S2 File

(XLSX)

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S1 Checklist

(DOC)

Click here for additional data file. (66.5KB, doc)

Data Availability

All relevant data are within the manuscript and its Supporting information files.

Funding Statement

The author(s) received no specific funding for this work.

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Decision Letter 0

Giuseppe Lucarelli

29 May 2022

PONE-D-22-03642Diagnostic Accuracy of Prognostic Nutritional Index as a Prognostic Factor for Renal Cell Carcinoma: A Systematic Review and Meta-AnalysisPLOS ONE

Dear Dr. Cho,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Partly

Reviewer #3: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #1: Yes

Reviewer #2: No

Reviewer #3: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Objectives: Authors aim for this systematic review and meta-analysis is to evaluate prognostic value of Prognostic Nutritional index by meta-analysis of the diagnostic test accuracy in kidney cancer.

There are some minor issues that need to be corrected before the manuscript can be published.

1. The title of the introduction section should be modified (Itroduction)

2. The calculation formula of PNI is incorrect. I would ask the authors to correct it.

3. Figure 2 legend has a mistype error (“qualityof”)

4. In table 1 the authors wrote distal metastasis. Probably the authors meant distant. If it is the case, I would like to ask the authors to correct it.

5. In Figure 4 legend I believe that the acronym authors had intended to use is “SPEC” not “SEPC”. I would ask the authors to correct it.

Reviewer #2: In the current manuscript the authors evaluated the diagnostic accuracy of the prognostic nutritional index (PNI) for renal cell carcinoma (RCC) in a pooled-analysis fashion. Overall the topic is interesting and timely, however, it is not new. Other groups reported SR & MA on PNI (DOI: 10.3389/fonc.2021.719941 - DOI: 10.1016/j.urolonc.2021.05.028) reaching the conclusion that PNI could be considered a potential prognostic predictor of treatment outcomes for patients with RCC. Neverthless, the authors of the current SR tried to slice the topic evaluating the diagnostic accuracy level only.

Please find below some observation from my side.

Abstract. Please remove the sentences "However, the prognostic value of PNI in RCC remains unclear.". It is absolutely not supported by the available literature.

Abstract. Could authors clarify the period of paper collecting.

Introduction. This sentence " Several prognostic factors for renal cell carcinoma (RCC) have been established, including the pathologic T stage, Fuhrman nuclear grade, tumor size, lymph node metastasis, and distant metastasis" needs strong references, indeed, the role of some of cited parameters are still under debate.

Introduction. Could the author add a reference here "However, conflicting results have been reported regarding the utility of the PNI in patients with RCC, due to differences among studies in sample size, presence of metastasis, patient characteristics, and other factors."

Introduction. A clear sentence about the aims of this study lacks.

M&M. Please the authors provide the PICOS.

Could the authors explain why they decided to include papers written in languages other than English. How were the articles traslated?

M&M. The statistical analysis is reported in a remarkable way! Howeveer, the lack of RCT and High-level studies is a crucial negative-point.

Results. Did the authors consider to evaluate ASA >2 patients as subgrup for the analysis? Please the authors report how to decide the variable for subgroup analysis.

Discussion. Please absolutEly remove this sentences since they are not point of streight, but the normal way for addressing a SR-MA "The strengths of this study included the comprehensive literature search strategy based on a standardized protocol. Furthermore, rigorous data analysis methods were applied, such as bivariate random-effects meta-analysis (including covariates) and ROC curve analysis."

Discussion. I believe that the discussion is the place where discuss about the results of analysis in a critical way. It is not the place where cut and paste the results of other work or talk about random arguments. Please handle it again.

Conclusion. The conclusions are not supported by the results. They are not in line with the study aim that are to demonstrate the diagnostic accuracy of PNI as a prognostic factor for RCC

References. They are up-to-date. However, several sentences in the manuscript lack references.

Table and Figures. They are of good quality.

Please a native speacker check is straight reccomanded.

Reviewer #3: In this meta-analysis, the authors evaluated the role of the PNI as a prognostic factor for RCC.

I have some comments:

- Please rephrase the title and the text when you use the term "diagnostic" in association with "prognostic". For example in the title "diagnostic accuracy...as prognostic factor". Diagnosis and prognosis are different processes of medical evaluation. Please remove the term "diagnostic", in this study it has been evaluated the prognostic role of PNI.

-A prognostic role has been proposed for other circulating biomarkers associated with different features of RCC biology, including carbonic anhydrase IX (CAIX), hypoxia-inducible factor-1α (HIF1α), CA15-3, PTX3, and C-reactive protein (CRP) (ref:PMID: 15126876; PMID: 24692843; PMID: 32345771;PMID: 20006861)

These studies should be referenced and discussed.

-RCC is a metabolic disease characterized by a reprogramming of energetic metabolism. In particular the metabolic flux through glycolysis is partitioned (PMID: 30983433, PMID: 29371925, PMID: 28933387; PMID: 30538212), and mitochondrial bioenergetics and OxPhox are impaired , as well as lipid metabolism (PMID: 30538212; PMID: 32861643). In addition a recent study (PMID: 33322148) delineated a lipidomic profile of human ccRCC and integrated it with transcriptomic data to connect the variations in cancer lipid metabolism with gene expression changes. These findings should be referenced and discussed.

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Reviewer #1: Yes: Tataru Octavian Sabin

Reviewer #2: No

Reviewer #3: No

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PLoS One. 2022 Aug 5;17(8):e0271821. doi: 10.1371/journal.pone.0271821.r002

Author response to Decision Letter 0

6 Jul 2022

Thank you for your constructive comments and suggestions. We reviewed our manuscript and did all our best to revise the manuscript as you suggested. Those are as follows:

Reviewer #1:

1) The title of the introduction section should be modified (Itroduction)

Answer

We thank the reviewer for this comment. We changed “Itroduction” to “Introduction” as reviewer suggested.

2) The calculation formula of PNI is incorrect. I would ask the authors to correct it.

Answer

We thank the reviewer for this important comment. We corrected the calculation formula of PNI as reviewer suggested.

3) Figure 2 legend has a mistype error (“qualityof”)

Answer

We thank the reviewer for this comment. We changed “qualityof” to “quality of” as reviewer indicated.

4) In table 1 the authors wrote distal metastasis. Probably the authors meant distant. If it is the case, I would like to ask the authors to correct it.

Answer

We thank the reviewer for this comment. We changed “distal” to “distant” as reviewer suggested.

5) In Figure 4 legend I believe that the acronym authors had intended to use is “SPEC” not “SEPC”. I would ask the authors to correct it..

Answer

We thank the reviewer for this comment. We changed “SEPC” to “SPEC” as reviewer indicated.

Reviewer #2:

1) Abstract. Please remove the sentences "However, the prognostic value of PNI in RCC remains unclear.". It is absolutely not supported by the available literature.

Answer

We thank the reviewer for this comment. We removed the sentences "However, the prognostic value of PNI in RCC remains unclear." In the abstract part of manuscript.

2) Abstract. Could authors clarify the period of paper collecting?

Answer

We thank the reviewer for this comment. To comply with the reviewer’s recommendations, we clarified the period of paper collecting in the abstract part of manuscript.

3) Introduction. This sentence " Several prognostic factors for renal cell carcinoma (RCC) have been established, including the pathologic T stage, Fuhrman nuclear grade, tumor size, lymph node metastasis, and distant metastasis" needs strong references, indeed, the role of some of cited parameters are still under debate.

Answer

We thank the reviewer for this important comment. To comply with the reviewer’s recommendation, we added references. In addition, we revised the sentence “have been established” to “have been established or under estimation”.

4) Introduction. Could the author add a reference here "However, conflicting results have been reported regarding the utility of the PNI in patients with RCC, due to differences among studies in sample size, presence of metastasis, patient characteristics, and other factors."

Answer

We thank the reviewer for this pertinent comment. To comply with the reviewer’s recommendations, we added references. In addition, we revised the term “conflict” to “insufficient”.

5) Introduction. A clear sentence about the aims of this study lacks.

Answer

We thank the reviewer for this important comment. To comply with the reviewer’s recommendations, we inserted the sentence “The aim of current study is to complete meta-analysis for diagnostic performance of PNI for the prediction of recurrence or survival in RCC patients, in order to provide more evidence-based data of PNI as a prognostic factor in RCC patients.” In the introduction part of manuscript.

6) M&M. Please the authors provide the PICOS.

Answer

We thank the reviewer for this pertinent comment. To comply with the reviewer’s recommendations, we inserted the sentence “Initial screening of search results based on titles and abstracts was performed based on structured questions using the PICO methodology: Populations: patients with RCC; Intervention: high PNI value; Comparator: low PNI value; Outcomes: survival” In the Methods part of manuscript.

7) Could the authors explain why they decided to include papers written in languages other than English. How were the articles traslated?

Answer

We thank the reviewer for this important comment. We tried to include all possible data because there were only a few papers about this topic. Therefore, we tried to include papers written in lanaguages other than English but unfortunately there was no suitable paper included in this study.

8) M&M. The statistical analysis is reported in a remarkable way! Howeveer, the lack of RCT and High-level studies is a crucial negative-point.

Answer

We thank the reviewer for this pertinent comment. We totally agree with the reviewer’s opinion. Therefore, we described it as a limitation point of this study in the discussion part of manuscript.

9) Results. Did the authors consider to evaluate ASA >2 patients as subgrup for the analysis? Please the authors report how to decide the variable for subgroup analysis..

Answer

We thank the reviewer for this important comment. To comply with the reviewer’s recommendations, we performed subgroup analysis with ASA >2 patients. As a result of statistical analysis, there was no significant difference between ASA >2 group and ASA ≤2 group. In addtion, there were only 4 out of 11 studies showing ASA or ECOG score and limitation to the analysis. We described it in the result part of manuscript. We tried to perform subgroup analysis with variables for which data from all papers were available. As a result, these variables such as ethnicity, sample size, presence of metastasis, PNI cut-off value, QUADAS-2 classification, and proportion of males were included.

10) Discussion. Please absolutEly remove this sentences since they are not point of streight, but the normal way for addressing a SR-MA "The strengths of this study included the comprehensive literature search strategy based on a standardized protocol. Furthermore, rigorous data analysis methods were applied, such as bivariate random-effects meta-analysis (including covariates) and ROC curve analysis."

Answer

We thank the reviewer for this pertinent comment. To comply with the reviewer’s recommendations, we removed the sentences "The strengths of this study included the comprehensive literature search strategy based on a standardized protocol. Furthermore, rigorous data analysis methods were applied, such as bivariate random-effects meta-analysis (including covariates) and ROC curve analysis." In the discussion part of the manuscript.

11) Discussion. I believe that the discussion is the place where discuss about the results of analysis in a critical way. It is not the place where cut and paste the results of other work or talk about random arguments. Please handle it again.

Answer

We thank the reviewer for this important comment. To comply with the reviewer’s recommendation, we removed the sentence “We previously reported that a low PNI was strongly associated with tumor progression and poor prognosis in patients with non-metastatic RCC” and added the sentence “Therefore, the PNI can aid clinicians in predicting the clinical outcomes of RCC and patients with low PNI need to be managed by nutritional support and treated in a way to correct malnutritional status.” In the discussion part of the manuscript.

12) Conclusion. The conclusions are not supported by the results. They are not in line with the study aim that are to demonstrate the diagnostic accuracy of PNI as a prognostic factor for RCC

Answer

We thank the reviewer for this pertinent comment. To comply with the reviewer’s recommendations, we changed the sentence “In conclusion, the results of this study demonstrate that the PNI has value as a prognostic factor for RCC to “In conclusion, the results of this study demonstrate that diagnostic accuracy of the PNI as a prognostic factor for patients with RCC”.

13) References. They are up-to-date. However, several sentences in the manuscript lack references.

Answer

We thank the reviewer for this important comment. To comply with the reviewer’s recommendations, we added references in the sentences of the manuscript.

14) Table and Figures. They are of good quality.

Answer

We appreciate your trying to encourage us.

15) Please a native speacker check is straight reccomanded.

Answer

We thank the reviewer for this pertinent comment. However, our manuscript has already been qualified by an accredited institution. We attach the certificate file separately.

Reviewer #3:

1) Please rephrase the title and the text when you use the term "diagnostic" in association with "prognostic". For example in the title "diagnostic accuracy...as prognostic factor". Diagnosis and prognosis are different processes of medical evaluation. Please remove the term "diagnostic", in this study it has been evaluated the prognostic role of PNI.

Answer

We thank the reviewer for this important comment. To comply with the reviewer’s recommendations, we removed the words “diagnostic accuracy of” from the title. However, this study is diagnostic test accuracy meta analysis and it is different from general meta analsysis in a method for statistical analysis. Therefore, we think it would be better to leave the word in an essential part of the text.

2) A prognostic role has been proposed for other circulating biomarkers associated with different features of RCC biology, including carbonic anhydrase IX (CAIX), hypoxia-inducible factor-1α (HIF1α), CA15-3, PTX3, and C-reactive protein (CRP) (ref:PMID: 15126876; PMID: 24692843; PMID: 32345771;PMID: 20006861)

These studies should be referenced and discussed.

Answer

We thank the reviewer for this pertinent comment. To comply with the reviewer’s recommendations, we specifically discuss of circulating biomarkers associated with different features of RCC biology at the discussion section of the manuscript.

3) RCC is a metabolic disease characterized by a reprogramming of energetic metabolism. In particular the metabolic flux through glycolysis is partitioned (PMID: 30983433, PMID: 29371925, PMID: 28933387; PMID: 30538212), and mitochondrial bioenergetics and OxPhox are impaired , as well as lipid metabolism (PMID: 30538212; PMID: 32861643). In addition a recent study (PMID: 33322148) delineated a lipidomic profile of human ccRCC and integrated it with transcriptomic data to connect the variations in cancer lipid metabolism with gene expression changes. These findings should be referenced and discussed.

Answer

We thank the reviewer for this important comment. To comply with the reviewer’s recommendations, we more specifically discuss metabolism of RCC mentioned by reviewer in the discussion part of the manuscript.

Attachment

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Decision Letter 1

Giuseppe Lucarelli

8 Jul 2022

Prognostic Nutritional Index as a Prognostic Factor for Renal Cell Carcinoma: A Systematic Review and Meta-Analysis

PONE-D-22-03642R1

Dear Dr. Cho,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Giuseppe Lucarelli, M.D., Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Giuseppe Lucarelli

27 Jul 2022

PONE-D-22-03642R1

Prognostic Nutritional Index as a Prognostic Factor for Renal Cell Carcinoma: A Systematic Review and Meta-Analysis

Dear Dr. Cho:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

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on behalf of

Dr. Giuseppe Lucarelli

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