Clinicopathological parameters
The median age of 280 patients was 60 years old (range 26 to 83 years old), with 114 patients (40.7%) aged >60 years. Among them, there were 143 men and 137 women. Primary manifestations of GISTs were as follows: abdominal discomfort or pain (n = 65), GI bleeding (n = 56), obstruction (n = 17), tumor perforation or rupture (n = 24), medical examination reported (n = 104), and other symptoms (n = 14). The primary tumor sites were mainly stomach (n = 182), secondly small intestine (n = 84), and colorectum or intraperitoneally with unknown origin in the next place (n = 14). The tumor size varied from 1.0 to 30.0 cm (median, 7.5 cm). 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.
Survival best cut-off analysis
According to the recent study, OPNI is a prognostic marker to GIST[23]. We used the continuous variable NLR, PLR and OPNI of 200 patients after PSM, and their RFS and outcome as the state variable. The cut-off point of OPNI is 42.6 (P<0.001), NLR is 5.1(P<0.001) and PLR is 98.6(P=0.008). Exp (coef), univariate P-value and Hazard ratio of NLR, PLR and OPNI were summarized in Table 2, Figure 1.
Correlation analysis
As we saw in Spearman Correlation analysis, higher OPNI was associated with primary tumor site of stomach(P<0.01), smaller tumor size (P<0.017), lower mitotic index (P<0.001), lower modified NIH risk classification (P<0.001), less gastrointestinal bleeding rate(P<0.01) and tumor rupture(P<0.01) and much lower tumor relapse rate(P<0.01). A strong correlation was observed between NLR and tumor site(P=0.01), GI bleeding(P<0.01), tumor rupture(P=0.03) and relapse(P=0.02). And PLR was also connected with tumor site(P<0.01), GI bleeding(P=0.04) and relapse(P=0.03). (Table 3, Figure 2 and Table 4)
Evaluation of the PS Model
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). This was calculated by Kaplan-Meier method, we concluded that our estimated median follow-up time was 47.98 months(P<0.001).
Univariate survival analysis
Our univariate survival analysis showed that tumor size (Log-rank P =0.002), mitotic index (Log-rank P <0.001), modified NIH risk stratification (Log-rank P <0.001), Ki-67 index (Log-rank P =0.053), age (Log-rank P =0.005) and OPNI (Log-rank P =0.002) were all significant prognostic parameters for RFS. Results of univariate survival analysis are in Table 5.
Multivariate survival analysis
Some sorted factors were analyzed in the Cox proportional hazards model in enter strategies. The results of the Cox regression analysis are listed in Table 5. High mitotic index (P=0.001), age more than 60(P=0.020), larger tumor size(P=0.007), high NLR (P=0.033), and low OPNI (P=0.007) were statistically significant independent negative prognostic indicators for RFS.
Survival analysis
We divided patients with or without medical treatment into several groups according to relatively low or high OPNI, NLR and PLR. And we observed that patients who used TKIs had a better relapse free survival. In addition, patients with higher OPNI showed preferable RFS than those with lower OPNI (P<0.0001). Furthermore, higher NLR (P<0.0001) and PLR (P=0.0003) were factors leading to poor prognosis (Figure 3).