Objective The aim of this prospective study was to evaluate the changes in the ovarian reverse after myomectomy based on serum anti-Mullerian Hormone (AMH) levels. Methods This is a prospective longitudinal observational study. Serum AMH levels were measured at the baseline and 2 day , 3months after myomectomy in 35 women aging from 36 to 45years.Follicle stimulate hormone(FSH) and luteal hormone(LH) were measured at the same time. 35 women of the same age with fibroid who did not undergo operation were selected as control group. Result (1)AMH level is (1.54 ± 0.95)ng/mL,(1.18 ± 0.77)ng/mL,(1.50 ± 0.58 )ng/mL at 0 day, 2 days and 3 months after operation. AMH level decreased significantly at 2 days after operation (P < 0.05) and increased gradually 3 months after operation, but showed no significant change (P > 0.05).(2) Significant differences in the serial change of AMH levels existed at each time point between myomectomy group and control group (P <0.05). No significant differences in FSH or LH levels existed at each time point. Conclusion AMH is may be superior to FSH or LH in evaluating the changing of ovarian reverse. The study suggests that myomectomy affect the ovarian function for up to 3 months post-operatively , and hemorrhage during and after operation may decrease serum AMH levels.

Objective To evaluate the value of the new ovarian function marker serum anti-Mullerian hormone (AMH)and to clarify the effect of hysterectomy on the ovarian function of the younger women.Methods The serum AMH,follicle stimulating hormone (FSH)and luteinizing hormone (LH)levels in 35 women suffered uterus benign lesion aged 36-45 years and 35 women suffered hysteromyoma without operation were measured at different time.And the ovarian arterial blood flow resistance index (RI ) was measured by Doppler ultrasound. Results Compred with before operation, the serum AMH levels of the patients in hysterectomy group 2 d and 3 months after operation were significantly decreased (P<0.05 or P<0.01).Compared with control group,the serum AMH levels of the patients in hysterectomy group 2 d and 3 months after operation were also decreased (P<0.05).The ovarian arterial blood flow RI of the patients in hysterectomy group 1 and 3 months after operation were increased compared with control group (P<0.05).There were no significant differences in the serum FSH and LH levels in each group between different time points (P>0.05).Conclusion Hysterectomy can affect the ovarian function,and the serum AMH level 3 months after operation is decreased and the ovarian arterial blood flow RI is increased.AMH is superior to FSH or LH in evaluating the changes of ovarian function.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.

Objective:To analyze the influencing factors of platinum resistant recurrence in advanced epithelial ovarian cancer(AEOC),establish a nomogram model to predict platinum-resistant recurrence of AEOC,and inter-nally validate it.Methods:The clinicopathological data of 577 AEOC patients who achieved complete remission af-ter initial treatment in the Department of Gynecology,Yunnan Cancer Hospital from June 1,2013 to December 31,2021 were collected.According to whether the platinum free interval(PFI)was less than 6 months,the patients were divided into platinum-resistant recurrence group(130 cases)and non-platinum-resistant group(447 cases,including patients with platinum-sensitive recurrence and no recurrence after 6 months of follow-up).Multivariate Logistic regression analysis was used to screen for the independent risk factors affecting the recurrence of plati-num-resistant patients.Based on the independent risk factors,a nomogram prediction model was established,and Bootstrap method was used for internal verification.The area under the ROC curve(AUC),calibration curve and decision curve(DCA)were used to evaluate the performance of the model.Results:①There were statistically sig-nificant differences in age,bilateral ovarian invasion,FIGO staging,menopause,neoadjuvant chemotherapy(NACT),chemotherapy interval(TTC),platelet count(PLT),platelet count/lymphocyte count ratio(PLR),fibrino-gen/lymphocyte count ratio(FLR),prognostic nutritional index(PNI),albumin(ALB),CA125 level,ascites volume,residual lesions,perioperative chemotherapy frequency,and CA125 half-life between the two groups(P＜0.05).②Multivariate Logistic regression analysis showed that bilateral ovarian invasion,FIGO stage Ⅳ,TTC＞16 days,ini-tial ascites volume＞1000ml,perioperative chemotherapy frequency＞9 times,surgery with R2 resection,CA125 half-life＞52 days were independent risk factors for recurrence of platinum-resistant AEOC patients(OR＞1,P＜0.05).③The AUC of the nomogram model constructed based on the above 7 indicators was 0.791(95％Cl 0.747-0.835),and the calibration curve and ideal curve fitted well.DCA showed that the net benefit interval of the model was 0.037-0.800.Conclusions:The nomogram prediction model based on independent risk factors for the recurrence of platinum-resistance of AEOC patients has good discrimination,calibration and clinical appli-cability,which can better predict the recurrence risk of platinum-resistance in AEOC patients after the initial treat-ment.