| Objective: Pituitary neuroendocrine tumors(PitNETs)is a benign tumor originating from the anterior pituitary cells,which have highly variable cell lineage and diverse behavior.About one-third of patients have severe aggressive behaviors.The main clinical manifestations are tumor mass effect and(or)hormone secretion disorder,which seriously affect the living quality and life expectancy of patiens.Currently,surgical resection is the primary treatment option for most PitNETs patients.Therefore,identification of the growth behavior and proliferative potential of tumors before treatment can be conducive to formulating personalized clinical treatment and management approaches.The tumor proliferation marker of Ki-67 index is closely associated with the proliferative and aggressive potential of pituitary tumor cells,but can only be obtained by postoperative immunohistochemistry.The purpose of this study is to explore the relevant influencing factors of the high expression of Ki-67 index(Ki-67 ≥ 3%)in pituitary tumor tissue,establish a risk prediction model for preoperative prediction of Ki-67 index expression level ≥ 3%,and provide a certain reference value for the clinical diagnosis,treatment and management of patients.Methods: This study retrospectively incorporated 449 patients who first come to the Second Affiliated Hospital of the Army Military Medical University from January 2015 to December 2019 and were initially diagnosed as PitNETs by postoperative pathology.The 449 patients were randomly divided into a training set(n=314)and a validation set(n=135)at a ratio of 7:3 by the computer algorithm.Preoperative clinical data of all patients were collected and divided into low-level groups and high-level groups based on whether the Ki-67 index of tumor tissue was ≥ 3%.Firstly,single factor analysis,LASSO,and logistic regression analysis were used to screen the optimal predictors of Ki-67 ≥ 3% in the training set,and a nomogram prediction model was established based on the optimal predictors to assess the risk of Ki-67 ≥ 3% of pituitary tumor.The clinical utility of the prediction model was evaluated by the area under the receiver operating curve(ROC-AUC),calibration curve and clinical decision curve analysis(DCA).Perform external validation in the validation set.Results: 1.A total of 449 PitNETs patients were included in this study,including 229 female patients(51%)with an average age of 48.78 ± 12.88 years,and 108 patients(24.05%)with Ki-67≥3%.Among them,108 patients(24.05%)had tumor tissue Ki-67≥3%.There was no statistically significant difference in clinical data between the training set and the validation set(P>0.05).2.Among the 449 patients,the patients in the high-level group(Ki-67≥3%)were more prone to present mass effect than those in the low-level group(Ki-67<3%).At the same time,compared to patients with the low-level group,the patients with high-level group the age of onset was smaller,the maximum tumor diameter was larger,and the ability of the tumor to invade the cavernous sinus was stronger.The results of endocrine hormone test showed that free thyroxine(FT4)and luteinizing hormone(LH)were significantly decreased in the high-level group,but the prolactin(PRL)level was higher.The difference was statistically significant(P<0.05).3.In the training set,LASSO regression and Logistic regression analysis showed that age,the maximumtumor diameter,and FT4 level were independent predictors of tumor Ki-67≥3%.Among them,age(OR: 0.97,95% CI: 0.95-0,P=0.013)and preoperative serum FT4 level(OR: 0.93,95% CI: 0.87-0,P=0.034)were independent protective factors for tumor Ki-67≥3%,while the maximum tumor diameter(OR: 1.56,95% CI: 1.21-2.03,P<0.001)was an independent risk factors for tumor Ki-67≥3%.4.Based on the three independent predictors,a nomogram risk prediction model for PitNETs patients with Ki-67 index ≥3% was constructed.The ROC-AUC of the model in the training set and the validation set are 0.692(95%CI: 0.63 ~ 0.76)and 0.691(95%CI: 0.59 ~ 0.79),respectively.The calibration curves of the two groups show that the predicted value and the measured value fit well.The clinical decision curve has a net return rate within the threshold range of 0.10 ~ 0.35 and 0.20 ~ 0.45 respectively.Conclusion: The nomogram risk prediction model based on the age,maximum tumor diameter,and preoperative serum FT4 level of the patients with PitNETs has good discrimination,calibration,and clinical practicality,which can better predict the risk of tumor Ki-67≥3% in PitNETs patients before surgery,providing important reference and guidance for individualized treatment and management scheme for patients.Objective: Nonfunctioning pituitary neuroendocrine tumors(NF-PitNETs)refer to pituitary tumors that lack clinical symptoms or biochemical evidence of hormone hypersecretion.The main manifestations are pituitary mass effects(such as headache,dizziness,visual impairment,and hypopituitarism).However,about 40% of NF-PitNETs patients have elevated serum prolactin(PRL)levels during the disease.At present,the pathogenesis of NF-pit NETs with hyperprolactinemia has not been fully illustrated.The purpose of this study is to analyze the clinical data of NF-PitNETs patients with hyperprolactinemia and try to reveal the clinical characteristics and related influencing factors of hyperprolactinemia in NF-PitNETs patients.Methods: This study collected 370 patients who underwent surgical treatment and were diagnosed with NF-PitNETs from January 2015 to December 2019.The clinical data of all patients were collected,including general clinical data and imaging parameters,as well as histopathological results of postoperative tumor tissues.All statistical analyses were performed using SPSS and R studio software.Results: 1.Among 370 patients with NF-PitNETs,162(43.78%)had hyperprolactinemia.Compared with patients with normal PRL levels,the incidence of pituitary apoplexy was higher in the elevated PRL group(26.55% vs.17.79%,P= 0.042).2.In all patients,NF-PitNET patients in the elevated PRL group had a younger age of onset and a higher proportion of female patients.Laboratory biochemical indicators showed that the levels of glycated hemoglobin(Hb A1c),creatinine(CREA),uric acid(UA),testosterone(TESTO),luteinizing hormone(LH)and free thyroxine(FT4)in the elevated PRL group were significantly lower than in the normal PRL group,and the expression level of growth hormone(GH)was higher than the normal PRL group.The proportion of tumor proliferation marker ki-67≥3% increased significantly,and the difference was statistically significant(P<0.05).There were no significant differences in body mass index(BMI),history of hypertension and diabetes,maximum tumor diameter,and tumor invasive potential between the two groups.3.Multivariate Logistic regression analysis showed that age,female,the preoperative serum FT4 level and Ki-67≥3% were independent influencing factors for NF-PitNETs with hyperprolactinemia.Among them,age(OR: 0.97,95%CI: 0.95-0.99,P=0.002)and FT4 level(OR: 0.89,95%CI: 0.84-0.95,P=0.005)were independent protective factors for NF-PitNETs with hyperprolactinemia,while female(OR: 2.95,95%CI: 1.84-4.78,P<0.001)and the tumor Ki-67≥3%(OR:1.87,95%CI: 1.10-3.19,P=0.020)were independent risk factors for NF-PitNETs combined with hyperprolactinemia.Conclusion Patients with NF-PitNETs combine with hyperprolactinemia were more likely to have pituitary apoplexy.At the same time,among patients with NF-PitNETs,female patients,younger age at diagnosis,lower serum FT4 level,and tumor proliferation marker Ki-67≥3% have a higher risk of hyperprolactinemia. |
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