Objective:To investigate the clinical efficacy and safety of radiotherapy combined with pyrotinib for human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients with brain metastasis.Methods:A retrospective cohort study was conducted. The clinical data of 36 HER2-positive breast cancer patients with brain metastasis admitted to Shanxi Province Cancer Hospital from January 2021 to January 2023 were retrospectively analyzed. According to the different treatment methods, the patients were divided into the observation group and the control group, 18 cases in each group. The control group was treated with radiotherapy alone, and the observation group was treated with radiotherapy combined with pyrotinib. The objective remission rate, the disease control rate and the incidence of adverse reactions of both groups were compared; Kaplan-Meier method was used for survival analysis.Results:All patients were female and received trastuzumab or trastuzumab combined with pertuzumab chemotherapy or neoadjuvant therapy. The objective response rate of and disease control rate of in the observation group were higher than those in the control group [83.33% (15/18) vs. 50.00% (9/18), 94.44% (17/18) vs. 66.67% (12/18)], and the differences were statistically significant (χ 2 = 4.71, P = 0.034; χ 2 = 4.43, P = 0.034). The incidence of diarrhea in the observation group was higher than that in the control group [55.56% (10/18) vs. 16.67% (3/18), P = 0.035]. However, there were no statistically significant differences in the incidence of nausea, fatigue, and stomatitis between the 2 groups ( P = 1.000). The median progression-free survival (PFS) time in the observation group and the control group was 14.38 months and 12.08 months, respectively, and the difference in PFS was statistically significant ( P = 0.040). The median overall survival (OS) time in the observation group and the control group was 15.78 months and 11.19 months, respectively, and the difference in OS was statistically significant ( P = 0.034). Conclusions:Radiotherapy combined with pyrotinib is effective in the treatment of HER2-positive breast cancer patients with brain metastasis. It has no serious side effects, and can prolong the survival time of patients.

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.

Erythropoietic protoporphyria （EPP） is a rare inherited metabolic disease that often involves skin， blood， and nervous systems， and EPP with the main manifestations of severe liver damage and acute abdominal pain is extremely rare. By reviewing the clinical data and genetic testing results of a patient with EPP， this article discusses the clinical features and pathogenic genes of this disease， in order to improve the understanding of the disease among hepatologists and achieve early diagnosis and treatment.

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.