Prognostic value of Onodera’s Nutritional Index for intermediate and high risk gastrointestinal stromal tumors treated with or without TKIs

Immunoinammatory and nutritional markers such as peripheral blood neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and onodera’s prognostic nutritional index (OPNI) have gained considerable attention and revealed preliminaryly as prognostic markers in gastrointestinal stromal tumor (GIST).


Background
Gastrointestinal stromal tumor (GIST) is the most common mesenchymal tissue neoplasms of digestive system. It often occurs in stomach and small intestine, accidentally found in abdominal and pelvic, omentum, colorectal, esophagus, pancreas, etc [1]. According to literatures, the incidence of GIST is about 0.001%~0.0015% [2], which only accounts for a small part of gastrointestinal tumors. And the elderly suffer more. GIST is now considered to originate in the interstitial cell of Cajal, and the most common cause is mutations in receptor tyrosine kinases, especially among adults with proto-oncogene c-kit and plateletderived growth factor receptor A (PDGFRA) [3]. Treatment methods for GIST are relatively limited because it is not sensitive to radiotherapy and chemotherapy, so surgical resection is the rst choice, and is the only potentially curative therapy. Tyrosine kinase inhibitors (TKIs) are used as routine clinical drugs for GIST patients of medium to high risk due to their signi cant effects [4]. Despite the availability of TKIs such as imatinib mesylate (IM), which greatly promoted the disease-free survival (DFS), the relapse of GIST is common, even the tumors are R0 resected. So GIST is not easy to manage, let alone the prevalent side effects (fatigue, diarrhea, nausea, periorbital edema, muscle spasm, rash, etc) and resistance to IM. There are also approximately 15% of GIST patients are innately resistant or intolerant to rst-line imatinib treatment [5][6][7].Therefore, accurate risk classi cation schemes are becoming increasingly signi cant for screening out patients who are most possibly to bene t from systematic IM therapy. Nowadays, four widely accepted factors which can re ect the prognosis of GIST patients are tumor location, size, mitotic index and tumor rupture as suggested by National Institutes of Health (NIH) consensus criteria [8], Armed Forces Institute of Pathology (AFIP) criteria [9], and modi ed NIH consensus criteria [10]. As time goes by, more and more independent prognostic factors are proposed, such as antigen identi ed by monoclonal antibody Ki-67 index and surgery options [11,12], In addition, tumor-associated in ammatory cells, which consist tumor microenvironment, promote the proliferation, invasion and metastasis of tumor cells. Thus enhance the development and progression of tumor [13]. As many studies shown, GIST is also affected by immunoin ammatory factors such as peripheral blood neutrophil-to-lymphocyte ratio (NLR), as well as platelet-to-lymphocyte ratio (PLR) [14], which are readily measurable, reproducible and inexpensive systemic in ammatory marker. The that high level of NLR or PLR were reported to associate with poor prognosis of various solid tumors. However, investigations on the prognostic value of NLR and PLR for GISTs are lacking and the results remain controversial [15][16][17].Onodera's prognostic nutritional index (OPNI) was initially used to evalulate the immune-nutritional state of patients who are given gastrointestinal surgery [18]. Several studies have shown that the OPNI is a crucial prognostic factor in some speci c human cancers such as gastric cancer [19], pancreatic cancer [20], colorectal cancer [21] and esophageal cancer [22]. Recently, an article about OPNI and GIST illustrated that OPNI plays a crucial role in prediction for GISTs that were not treated with medicine [23]. However, whether OPNI is a prognostic marker for GIST treated with TKIs has not been expounded, and the predictability difference between GIST treated with or without TKIs remains unknown. In this study, we investigate this rstly.

Patients
We retrospectively retrieved the 563 cases of GIST ranging from the lowest to high risk according to the modi ed NIH risk classi cation, in Nanjing Drum Tower Hospital from January 2010 to December 2018.
Among them, 349 cases were not treated with TKIs, and the other 214 cases received TKIs therapy. In this study, we selected patients classi ed as the intermediate and high risk, and divided them into two groups: TKIs-using group and TKIs-unused group. We intended to investigate whether OPNI can be a prognostic marker to these two groups. The inclusion criteria was set as follows: (1)Classi ed as intermediate and high risk according to modi ed NIH risk classi cation; (2) primary localized GISTs with R0 resection; (3) no other synchronous primary tumors; (4) complete medical records; (5) patients whose follow-up was done.
Eventually, 280 GISTs were enrolled in this investigation. Among them, 102 patients received no therapies of imatinib, while 178 patients were treated by imatinib after operation. This study was approved by the Ethics Committee of Nanjing Drum Tower Hospital. And written informed consent was acquired from all the patients in this program.
Preoperative peripheral blood routine tests and OPNI evaluation All the results of preoperative peripheral blood routine and blood biochemistry were obtained within 5 days before surgery. The NLR value was calculated as neutrophil count (10 9 /L) divided by the lymphocyte count (10 9 /L). The value of platelet-to-lymphocyte ratio (PLR) was calculated same as NLR. The OPNI was calculated as serum albumin (g/L) + 5×total lymphocyte count (10 9 /L).

Clinicopathological features
All GISTs were initially diagnosed as gastrointestinal mesenchymal tumors by pathological ways based on a combination of histopathological evaluation and immunohistochemistry for CD117 or Discovered On GIST 1 (DOG1). They are further con rmed by CD34, desmin, SMA, S-100 expression. DNA mutation analysis of PDGFRA gene exons 12 and 18 or c-kit gene exons 9, 11, 13 and 17 were also made to determine the application of TKIs. In this study, clinical data and histopathological parameters are all collected from medical records. Clinical data includes age, gender, initial complaint, primary tumor site, tumor size, surgery options, tumor rupture (preoperative or intraoperative) , whether the TKIs were used and hospitalization time.
Tumor size was accurately measured by pathologists after surgery. Histopathological factors include predominant cell type (spindle, epithelioid, or mixed), mitotic index (per 50 randomly selected high power elds [HPFs]), tumor necrosis and Ki-67 index. Risk strati cation of each case was determined by modi ed NIH consensus criteria covering tumor size, mitotic index, tumor site, and rupture.

Follow-up
The patients after surgery were followed up through routine peripheral blood tests, abdominal ultrasonography, endoscopy and computed tomography (CT) every 6 months in the rst 5 years, and then annually after 5 years to evaluate tumor recurrence or distant metastasis. Follow-up information was obtained by outpatient or hospitalized records , or direct contact with patients or their family. Relapse-free survival (RFS) is more suitable to evaluate patients' survival than overall survival (OS). RFS was calculated from the date of surgery to the date of GIST relapse, metastasize or to the last follow-up date,.

Statistical analysis
All statistical analyses were calculated by using IBM SPSS Statistics, version 22.0 (IBM, New York, USA). The ranked and unordered categorical variables were respectively assessed by Mann-Whitney U and Chi-square test. The correlation of continuous variables was calculated by Pearson correlation coe cient, while discrete variables by Spearman's correlation coe cient. Cox's regression model was used to perform multivariate survival analyses. The log-rank test and Kaplan-Meier method were utilized to calculate univariate survival.
The PLR, NLR, OPNI cut-off value was determined according to the receiver operating characteristic (ROC) curve analysis, which was performed based on the recurrence state at 9-year follow-up. The Youden indexwas estimated to determine the optimal cutoff value for PLR, NLR and OPNI, calculated as sensitivity -(1 -speci city). A P-value <0.05 was indicated to be statistical signi cant, and con dence intervals (CI) were calculated at the 95 % level.
In this study, we applied 1:1 propensity score matching to adjust patients for gender, age, primary tumor site, tumor size, mitotic index and risk strati cation in order to reduce the effect of potential confounding factors and selection bias, such as patients' baseline clinicopathologic factors or unequal patients distribution between the TKIs-used and TKIs-unused groups. A 0.05-width caliper of the standard deviation of the logit was set to match the two groups.

Clinicopathological parameters
The median age of 280 patients was 60 years old (range 26 to 83 years old), with 114 patients (40.7%) aged Histologically, the spindle cell type was most common (n = 162), followed by epithelioid cell type (n = 12) and mixed type (n = 6). The mitotic index, necrosis, and more detailed clinicopathological variables of our patients before and after PSM are summarized in Table 1.

ROC analysis
According to the recent study, OPNI is a prognostic marker to GIST [23]. We used the continuous variable NLR, PLR and OPNI of 349 patients who did not receive any preoperative or postoperative therapies of imatinib as test variables, and RFS as the state variable. The cut-off point of OPNI is 44.05 (P<0.001). Areas under the ROC curve (AUC), cut-off points, sensitivity, speci city, and Youden indexes of NLR, PLR and OPNI were summarized in Table 2, Figure 1. The Hosmer-Lemeshow test and the value of c-statistic (0.71) showed fairly excellent calibration (p = 0.08) and discrimination, respectively, between the 2 groups. The ASD values after matching ranged from 0 to 8%.

Follow-up
Patients were followed for a median of 48 months (Range: 8months-103months). 62 patients experienced tumor relapse during the follow-up period. Metastasis to the lymph nodes was not spotted.

Discussion
In this study, according to recent investigations of Sun JY's team that showed OPNI was an independent predictive factor of RFS in GIST patients with no TKIs treatment [23]. we initially base our analysis on the 349 patients who received no TKIs therapy, and get the cut-off points of NLR, PLR, OPNI and Ki-67 index. Then we examined the univariate and multivariate survival analysis of our patients after PSM study. It was our aim to investigate the prognostic value of OPNI in intermediate and high risk gastrointestinal stromal tumors treated with or without TKIs. Eventually, analysis proved that OPNI was an independent prognostic marker for both two groups. And predictability for those patients who did not receive TKIs treatment is better than that who received TKIs.
A more precise risk classi cation criterion that can be applied to determine the postoperative prognosis of patients with GIST is eagerly required. Of which the items should be simply and economically detected and calculated by clinicopathological data, Nowadays, the most widely used criterion to estimate the risk of relapse after surgery in GIST are the AFIP criteria, and modi ed NIH consensus criteria. Studies have proved that their prognostic accuracy is similar, by and large [24]. Moreover, Memorial Sloan-Kettering Cancer Center sarcoma team developed a nomogram that could estimate the probability of RFS at 2 and 5-year after surgery for primary GIST and was more precise than NIH criteria to a certain extent [25]. Joensuu H further demonstrated the KIT and PDGFRA mutations may have widely varying risks for recurrence, and those with KIT exon 11 duplication mutation or deletion of one codon have favorable RFS with surgery alone and are usually not candidates for adjuvant therapy [26].
OPNI is a nutrition index which is rstly raised by Onodera and his colleagues. The previous studies showed that patients with high OPNI shared a signi cantly better prognosis than those who had a lower value of OPNI [22]. And similar results regarding Crohn's disease and stage III colorectal cancer have been also reported [27,28]. In our study, the border value of the OPNI was determined to be 44.05 for TKIs-used group and TKIs-unused group according to ROC analysis. A detailed analysis demonstrated that lower OPNI was associated with primary tumor site, tumor size, mitotic index, tumor rupture and modi ed NIH risk classi cation. In multivariate survival analysis, OPNI was independent prognostic indicators. Low OPNI may result from low hypoproteinemia and/or lymphopenia, which can be explained by several potential phenomena: (1) nutritional supplementation of branched-chain amino acids can improve hypoproteinemia and reduce tumor recurrence in patient ; ( 2) lymphocytes play an important role in the host immune response, eliminating tumor formation and progression.
There does exist limitations of this study. Firstly, it is a single-center retrospective study, therefore, a multicenter study is eagerly required to enlarge the sample to minimize the de ciency during the analysis.
Secondly, the best cut-off value in this study is determined by the highest Yoden index by plotting the ROC curve. However, it is still unclear what cut-off value is the best optimal cut-off value for clinical diagnosis of GIST. In general, exploring the exact best cut-off value and studying its intrinsic molecular mechanism will be the future research direction.

Conclusions
We found connection among immuno-in ammatory, nutritional factors, clinico-pathological characteristics and the RFS of intermediate and high risk GIST treated with or without TKIs. OPNI is an independent indicator for RFS in GIST treated with or without TKIs, especially remarkable for TKIs-unused patients. Furthermore, OPNI also might be a ponderable factor for predicting tumor biological behavior from peripheral blood. This study has been approved by the Ethics Committees of Nanjing Drum Tower Hospital.

Consent for publication
No Availability of data and materials Access to the data and the calculation method can be obtained from the authors by email (fengwang36@163.com).

Competing of Interests
The authors declare that they have no competing of interests.