全膝关节置换术后膝关节功能康复个体化列线图预测模型的建立与验证

目的 进行全膝关节置换术（TKA）后膝关节功能康复个体化列线图预测模型的建立与验证。方法 选取2019年1月至2021年12月复旦大学附属上海市第五人民医院接收的150例膝骨关节炎病人为建模组。选取2020年1月至2021年12月该院接收的102例膝骨关节炎病人为验证组。将建模组病人分为康复不理想组（n=72）和康复理想组（n=78）。对建模组病人采用logistic回归法筛选影响TKA后膝关节功能康复不理想的危险因素;采用R软件构建预测TKA后膝关节功能康复不理想的列线图模型;用受试者操作特征（ROC）曲线评价模型区分度,校准曲线评估列线图模型一致性。结果 康复不理想组年龄≥65岁比例58.33%(42/72)、糖尿病比例41.67%(30/72)、未有软组织平衡术比例63.89%(46/72)、术后胫骨平台后倾角≥5°比例45.83%(33/72)、术前HSS评分<45分比例56.94%(41/72)、术后VAS评分≥6分比例62.50%(45/72)高于康复理想组[28.21%(22/78)、19.23%(15/78)、32.05%(25/78)、23.08%(18/78)...     

A novel nomogram to predict low anterior resection syndrome (LARS) after ileostomy reversal for rectal cancer patients

Background and aimLow anterior resection syndrome (LARS) in patients undergoing low or ultra-low anterior resection (LAR) is a common problem and significantly impacts the quality of life. Patients with an ileostomy after LAR are more likely to develop LARS. However, there hasn't been a model predicting LARS occurrence in these patients. This study aims to construct a nomogram to predict the probability of LARS occurrence in patients with temporary ileostomy and guide preventive strategies before reversal.Methods168 patients undergoing LAR with ileostomy from one center were enrolled as the training cohort, and 134 patients of the same inclusion criteria from another center were enrolled as the validation cohort. The training cohort was screened for risk factors for major LARS using univariate and multivariate logistic regression. The nomogram was constructed using the filtered variables, the ROC curve was used to describe the model's discrimination, and the calibration was used to describe the accuracy.ResultsThe optimal cut-off value for stoma closure time was 128 days. Three risk factors were identified using logistic regression analysis: preoperative radiotherapy (OR = 3.038, [95%CI 1.75–5.015], P = 0.005), stoma closure time (OR = 2.298, [95%CI 1.088–4.858], P = 0.029) and pN stage (OR = 1.739, [95%CI 1.235–3.980], P = 0.001). A nomogram was constructed based on these three variables and showed good performance predicting major LARS after stoma reversal. The area under the curve (AUC) was 0.827 in the training group and 0.821 in the validation group; The calibration curve suggested good precision in both groups.ConclusionsThis novel nomogram can accurately predict the probability of major LARS occurrence after ileostomy reversal for rectal cancer patients. This model can help screen ileostomy patients with high risks and guide individualized preventive strategies before stoma reversal.     

A Risk-scoring Model for Predicting Post-recurrence Survival in Patients With Endometrial Carcinoma

AimsThe survival time of patients with recurrent endometrial carcinoma is generally short. However, considerable interindividual variation exists. We developed a risk-scoring model for predicting post-recurrence survival in patients with endometrial carcinoma.Materials and methodsPatients with endometrial carcinoma treated at a single institution between 2007 and 2013 were identified. Pearson chi-squared analyses were used to compute odds ratios for the associations between risk factors and short survival after cancer recurrence. The results for biochemical analyses represented values at diagnosis of disease recurrence or values at initial diagnosis for those patients who had a primary refractory disease. Logistic regression models were constructed for the identification of variables that independently predict short post-recurrence survival. The models were used to assign points based on odds ratios for risk factors and risk scores were derived.ResultsIn total, 236 patients with recurrent endometrial carcinoma were included in the study. Based on overall survival analysis, 12 months was selected as the cut-off for short post-recurrence survival. Factors associated with short post-recurrence survival were platelet count, serum CA125 concentration and progression-free survival. A risk-scoring model with an area under the receiver operating characteristic curve (AUC) of 0.782 (95% confidence interval 0.713–0.851) was developed in patients without missing data (n = 182). When patients with a primary refractory disease were excluded, age and blood haemoglobin concentration were identified as additional predictors of short post-recurrence survival. For this subpopulation (n = 152), a risk-scoring model with an AUC of 0.821 (95% confidence interval 0.750–0.892) was developed.ConclusionsWe report a risk-scoring model that shows acceptable to excellent accuracy in predicting post-recurrence survival in patients with endometrial carcinoma, with primary refractory diseases included or excluded. This model has potential applications in precision medicine in patients with endometrial carcinoma.     

Clinicopathologic factors and preoperative ultrasonographic characteristics for predicting central lymph node metastasis in papillary thyroid microcarcinoma: a single center retrospective study

IntroductionThe treatment of papillary thyroid microcarcinoma remains controversial. Central lymph node metastasis is common in papillary thyroid microcarcinoma and it is an important consideration in treatment strategy selection.ObjectiveThe aim of this study was to investigate clinicopathologic risk factors and thyroid nodule sonographic characteristics for central lymph node metastasis in papillary thyroid microcarcinoma.MethodsWe retrospectively reviewed the data of 599 papillary thyroid microcarcinoma patients who underwent surgery from 2005 to 2017 at a single institution. Univariate and multivariate analyses were used to identify the clinicopathologic factors and preoperative sonographic features of central lymph node metastasis. A receiver-operating characteristic, ROC curve analysis, was performed to identify the efficacy of ultrasonographic features in predicting central lymph node metastasis. A nomogram based on the risk factors was established to predict central lymph node metastasis.ResultsThe incidence of central lymph node metastasis was 22.4%. The univariate and multivariate analyses suggested that gender, age, multifocality, extrathyroidal invasion, and lateral lymph node metastasis were independent risk factors for central lymph node metastasis. The univariate and multivariate analyses revealed that nodular shape, margin, and calcification were independently associated with central lymph node metastasis. The ROC curve analysis revealed that the combination of shape, margin and calcification had excellent accuracy in predicting central lymph node metastasis. The nomogram was developed based on the identified risk factors for predicting central lymph node metastasis, and the calibration plot analysis indicated the good performance and clinical utility of the nomogram.ConclusionsCentral lymph node metastasis is associated with male gender, younger age (<45 years), extrathyroidal invasion, multifocality and lateral lymph node metastasis in papillary thyroid microcarcinoma patients. The ultrasongraphic features, such as irregular shape, ill-defined margin and calcification, may improve the efficacy of predicting central lymph node metastasis. Surgeons and radiologists should pay close attention to the patients who have these risk factors. The nomogram may help guide surgical decision making in papillary thyroid microcarcinoma.     

抗结核药物所致肝损伤的不良反应分析及风险因素研究

目的探究抗结核药物(ATD)引发药物性肝损伤(DILI)的临床特征和危险因素,建立风险预测模型。方法以60例抗结核药物所致DILI的患者为观察组,以同期行相同方案治疗的结核病患者1100例作为对照组,采用回顾性分析手段对两组患者的一般资料、临床表现、实验室指标等数据,进行对比分析,找出ATD引起DILI的独立危险因素并利用R软件建立列线图风险预测模型。结果60例ATD引起DILI的不良反应报告中以女性为主,占58.33%;平均年龄为46.83±11.24岁,其中40~69岁发生率最高,占56.67%;临床分型中包括40例肝细胞损伤型,13例胆汁淤积型,7例混合型;临床表现以食欲下降、乏力最为显著。风险因素分析中,年龄、基础肝病、糖尿病、胆囊疾病、ALB、TBIL、含吡嗪酰胺、合用其他增加肝毒性药物为TB患者DILI的独立危险因素。R软件建立的列线图预测模型C-index指数高达0.902,说明本模型具有较好的预测能力。结论运用列线图模型评分预测发生DILI的风险,对结核病患者个体化化疗方案制定具有重要指导意义。     

Nomogram for predicting overall survival in patients with triple-negative apocrine breast cancer: Surveillance,epidemiology, and end results-based analysis

PurposeTriple-negative apocrine carcinoma (TNAC) is a sort of triple-negative breast cancer (TNBC) that is rare and prognosis of these patients is unclear. The present study constructed an effective nomogram to assist in predicting TNAC patients overall survival (OS).MethodsA total of 373 TNAC patients from the surveillance, epidemiology, and end results (SEER) got extracted from 2010 to 2016 and were divided into training (n = 261) and external validation (n = 112) groups (split ratio, 7:3) randomly. A Cox regression model was utilized to creating a nomogram according to the risk factors affecting prognosis. The predictive capability of the nomogram was estimated with receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA).ResultsMultivariate Cox regression analysis revealed age, surgery, chemotherapy, stage, and first malignant primary as independent predictors of OS. A prediction model was constructed and virtualized using the nomogram. The time-dependent area under the curve (AUC) showed satisfactory discrimination of the nomogram. Good consistency was shown on the calibration curves in OS between actual observations and the nomogram prediction. What's more, DCA showed that the nomogram had incredible clinical utility. Through separating the patients into groups of low and high risk group that connects with the risk system that shows a huge difference between the low-risk and high risk OS (P < 0.001).ConclusionTo predict the OS in TNAC patients, the nomogram utilizing the risk stratification system that is corresponding. These tools may help to evaluate patient prognosis and guide treatment decisions.     

乳腺癌化疗致周围神经病变的列线图模型构建与评价

目的 探讨乳腺癌患者化疗致周围神经病变（chemotherapy-induced peripheral neuropathy,CIPN）的影响因素,建立预测CIPN的列线图模型。方法 选择2019年7月至2022年1月福建省肿瘤医院治疗的431例乳腺癌化疗患者作为建模组,构建CIPN列线图模型;另选取89例乳腺癌患者作为验证组,比较两组患者的危险因素并绘制受试者工作特征曲线。结果 多因素分析显示：年龄、糖尿病、体质量指数（body mass index,BMI）、化疗前焦虑、化疗次数是CIPN的独立危险因素（P<0.05）;建模组和验证组的受试者工作特征曲线下面积分别为0.723（95%CI：0.676～0.770）和0.771（95%CI：0.676～0.866）。结论 本研究构建的列线图模型对乳腺癌化疗致周围神经病变的诊断具有较好的精确度和区分度。     

Survival prediction and conditional survival of primary central nervous system lymphoma: A population-based study

BackgroundPrimary central nervous system lymphoma is a rare and highly aggressive type of non-Hodgkin lymphoma. This study used population-based data to evaluate the clinical characteristics and prognostic factors of primary central nervous system lymphoma and develop a prediction model to estimate survival.MethodsPatients’ data were extracted from the Surveillance, Epidemiology, and End Results database. Significant prognostic factors were identified using univariate and multivariate Cox regression analyses. Conditional survival estimates were calculated as CS(x y) = S(x + y)/S(X), and a nomogram was built to predict patient prognosis.ResultsIn total, 2563 patients with primary central nervous system lymphoma were included. Multivariate Cox analysis showed that age at diagnosis, sex, histology, tumor site, surgery, chemotherapy, and marital status were independent prognostic factors of overall survival. The 1-year conditional survival increased with time, and our nomogram model showed favorable discriminative ability.ConclusionAt the population level, our study found that gross total resection and chemotherapy improved the prognosis of patients with primary central nervous system lymphoma. However, the prognosis of black patients was poor. Conditional survival provided a more accurate and dynamic survival estimate. Moreover, our nomogram had a good performance and could help predict the overall survival of these patients.     

中青年人群非酒精性脂肪肝发生风险预测模型的建立

目的建立非酒精性脂肪肝(NAFLD)的发生风险预测模型,为NAFLD的预防及发生提供管理策略。方法选取2015年1月至2018年7月大连医科大学附属第二医院健康管理中心年度体检数据库中18~59岁、至少有2次连续体检记录、基线未发生NAFLD且无重要指标缺失者的数据,观察结局为NAFLD。收集基本信息、体格检查、实验室检查和腹部超声检查资料,将所有研究对象随机分为建模组和验证组。采用SPSS 23.0进行χ²检验、t检验、秩和检验、单因素Cox回归分析。利用建模组资料进行多因素Cox回归分析选取预测指标,用RStudio软件绘制线图,构建NAFLD发生风险预测模型。通过一致性指数(C指数)和校正曲线对建模组和验证组模型的预测效果进行验证。结果本研究共纳入2377名研究对象,其中建模组1585人,验证组792人。本研究共有467人发生NAFLD(累积发病率为19.6%),平均随访时间为(27.06±8.02)个月。其中,建模组NAFLD发病人数为310人(发病率为19.6%),验证组NAFLD发病人数为157人(累积发病率为19.8%)。多因素Cox回归分析结果显示,高密度脂蛋白胆固醇水平(HR=0.334,95%CI:0.209~0.534)为NAFLD发病的独立保护因素,而体质指数(HR=1.220,95%CI:1.172~1.271)、甘油三酯(HR=1.114,95%CI:1.052~1.180)、低密度脂蛋白胆固醇(HR=1.252,95%CI:1.054~1.487)、丙氨酸氨基转移酶(HR=1.013,95%CI:1.005~1.021)、血尿酸(HR=1.003,95%CI:1.001~1.004)为NAFLD发病的独立危险因素(P<0.05,P<0.01)。利用上述影响因素成功构建NAFLD发生风险预测模型。建模组和验证组的C指数分别为0.789(95%CI:0.766~0.812)、0.777(95%CI:0.742~0.812),校正曲线显示模型预测结果与实际观察结果吻合良好。结论本研究构建的NAFLD发生风险预测模型可以准确地预测NAFLD的发生概率,为早期识别NAFLD高危人群提供新思路。     

Queratotomía arcuata transepitelial o intraestromal con láser de femtosegundo para corrección de astigmatismo corneal en el momento de la cirugía de cataratas

PurposeThe aim of this study was to compare the results of intrastromal arcuate incisions (AIs) and transepithelial AIs to treat corneal astigmatism during femtosecond laser-assisted cataract surgery (FLACS).MethodsThis retrospective study included 20 patients with corneal astigmatism between 0.70 and 2.00 diopters (D) who underwent FLACS with concurrent intrastromal AIs in one eye and transepithelial AIs in the fellow eye. The main outcomes measures at 2-3 months of follow-up were the difference between preoperative and postoperative keratometric corneal cylinder (Kcyl), the correction index (CI) and the percentage of overcorrection.ResultsThe mean difference between preoperative and postoperative Kcyl revealed a mean value of 0.36 ± 0.37 D in the transepithelial group and 0.53 ± 0.42 D in the intrastromal group (P < .001). The mean CI was 0.83 ± 0.71 in the transepithelial group and 0.68 ± 0.29 in intrastromal group (P = .17). Five eyes (25%) had an astigmatism overcorrection in the transepithelial group and 1 eye (5%) in the intrastromal group.ConclusionsBoth intrastromal and transepithelial AIs showed potential for mild to moderate astigmatism correction and appeared to be a safe procedure. Despite transepithelial AIs presented a higher CI, the intrastromal AIs results were more predictable.