预测小细胞肺癌一线化疗导致严重中性粒细胞减少的Nomogram的构建

目的 建立一个Nomogram来预测小细胞肺癌一线化疗引起严重中性粒细胞减少(3级或4级)的概率.方法 选择经组织学证实并接受一线化疗的小细胞肺癌患者263例纳入预测队列.在多变量Logistic回归分析中,采用前进法、后退法和逐步法的似然比检验,以最小赤池信息准则值作为停止准则,在此基础上绘制Nomogram;评估其...     

Predictors of overall and cancer-free survival of patients with localized prostate cancer treated with primary androgen suppression therapy: results from the prostate cancer outcomes study

PURPOSE: Primary androgen suppression therapy for clinically localized prostate cancer is increasingly common in the United States despite a lack of supportive evidence for its use. We determined which demographic and clinical factors predict overall and cancer specific survival with this treatment strategy in patients enrolled in the Prostate Cancer Outcomes Study. MATERIALS AND METHODS: In 1994 to 1995 the Prostate Cancer Outcomes Study recruited 3,533 men diagnosed with prostate cancer. Clinical and treatment information was abstracted from medical records and demographic characteristics were obtained from patient surveys 6, 12, 24 and 60 months after diagnosis. Overall and cancer specific mortality was analyzed through December 2002 using the Kaplan-Meier method and Cox regression. RESULTS: A total of 276 patients had organ confined (cT1-2) prostatic adenocarcinoma and received primary androgen suppression therapy within 1 year of diagnosis. Median followup for censored patients was 7.6 years (range 1.1 to 8.1). Five-year overall and cancer specific survival was 66% (95% CI 59-72) and 91% (95% CI 86-94), respectively. Independent predictors of shorter overall survival were patient age 75 years or older, prostate specific antigen 20 ng/ml or greater, Gleason score 7 or greater and abnormal digital rectal examination. Gleason score 7 or greater, prostate specific antigen 20 ng/ml or greater and a low comorbidity index were independent predictors of shorter cancer specific survival. CONCLUSIONS: The use of primary androgen suppression therapy in the Prostate Cancer Outcomes Study data set resulted in 91% 5-year cancer specific survival. Advanced age, and factors that reflect tumor burden and biology were predictive of overall survival, while cancer specific survival was predicted by tumor factors and the burden of comorbid conditions. A nomogram for predicting overall survival at 5 years was constructed.     

Standard versus limited pelvic lymph node dissection for prostate cancer in patients with a predicted probability of nodal metastasis greater than 1%

PURPOSE: We determined the yield of standard vs limited pelvic lymphadenectomy in patients with a predicted risk of lymph node metastasis greater than 1% according to the Partin tables predicted probability of pathological stage. We also determined the feasibility of laparoscopic standard pelvic lymph node dissection. MATERIALS AND METHODS: Of 1,269 patients with clinically localized prostate cancer undergoing radical prostatectomy, 648 had a Partin's table predicted probability of lymph node invasion greater than 1%. Of the 648 patients 177 underwent limited pelvic lymph node dissection performed laparoscopically (group 1), and 471 underwent standard pelvic lymph node dissection performed open (367) or laparoscopically (104) (group 2). Templates of limited pelvic lymph node dissection included the external iliac lymph nodes whereas standard pelvic lymph node dissection included the external iliac, obturator and hypogastric lymph nodes. Multivariate logistic regression analyses were performed to compare the node positivity rate between groups 1 and 2. RESULTS: On multivariate logistic regression analysis controlling for prostate specific antigen, biopsy Gleason sum, clinical stage and surgical approach, the odds of node positivity were 7.15-fold higher (95% CI 2.49-20.5, p<0.001) for standard vs limited pelvic lymph node dissection. The median (mean) number of nodes retrieved was 9 (10) and 14 (15) after limited and standard pelvic lymph node dissection, respectively (p<0.001). A similar impact was observed in patients treated laparoscopically with standard vs limited pelvic lymph node dissection (odds ratio 15.6, 95% CI 3.7-66.4, p<0.001). CONCLUSIONS: Standard lymph node dissection yields positive nodes more frequently and retrieves a higher total nodal count than the often performed pelvic lymph node dissection limited to the external iliac nodes. Standard pelvic lymph node dissection is feasible through a transperitoneal laparoscopic approach.     

Establishing and validating predictive nomograms for lateral pelvic lymph node metastasis in patients with rectal cancer based on radiologic factors and clinicopathologic characteristics

IntroductionIt is critical to accurately predict the occurrence of lateral pelvic lymph node (LPN) metastasis. Currently, verified predictive tools are unavailable. This study aims to establish nomograms for predicting LPN metastasis in patients with rectal cancer who received or did not receive neoadjuvant chemoradiotherapy (nCRT).Materials and methodsWe carried out a retrospective study of patients with rectal cancer and clinical LPN metastasis who underwent total mesorectal excision (TME) and LPN dissection (LPND) from January 2012 to December 2019 at 3 institutions. We collected and evaluated their clinicopathologic and radiologic features, and constructed nomograms based on the multivariable logistic regression models.ResultsA total of 472 eligible patients were enrolled into the non-nCRT cohort (n = 312) and the nCRT cohort (n = 160). We established nomograms using variables from the multivariable logistic regression models in both cohorts. In the non-nCRT cohort, the variables included LPN short diameter, cT stage, cN stage, histologic grade, and malignant features, and the C-index was 0.930 in the training cohort and 0.913 in the validation cohort. In the nCRT cohort, the variables included post-nCRT LPN short diameter, ycT stage, ycN stage, histologic grade, and post-nCRT malignant features, and the C-index was 0.836 in the training dataset and 0.827 in the validation dataset. The nomograms in both cohorts were moderately calibrated and well-validated.ConclusionsWe established nomograms for patients with rectal cancer that accurately predict LPN metastasis. The performance of the nomograms in both cohorts was high and well-validated.     

A Nomogram for Predicting Progression-free Survival in Patients with Endometrial Cancer

AimsEndometrial cancer is one of the most widely known gynaecological malignancies that lacks a prognostic prediction model. This study aimed to develop a nomogram to predict progression-free survival (PFS) in patients with endometrial cancer.Materials and methodsInformation for endometrial cancer patients diagnosed and treated from 1 January 2005 to 30 June 2018 was collected. The Kaplan–Meier survival analysis and multivariate Cox regression analysis were carried out to determine the independent risk factors and a nomogram was constructed by R based on analytical factors. Internal and external validation were then carried out to predict the probability of 3- and 5-year PFS.ResultsIn total, 1020 patients with endometrial cancer were included in the study and the relationship between 25 factors and prognosis was analysed. Postmenopause (hazard ratio = 2.476, 95% confidence interval 1.023–5.994), lymph node metastasis (hazard ratio = 6.242, 95% confidence interval 2.815–13.843), lymphovascular space invasion (hazard ratio = 4.263, 95% confidence interval 1.802–10.087), histological type (hazard ratio = 2.713, 95% confidence interval 1.374–5.356), histological differentiation (hazard ratio = 2.601, 95% confidence interval 1.141–5.927) and parametrial involvement (hazard ratio = 3.596, 95% confidence interval 1.622–7.973) were found to be independent prognostic risk factors; these factors were selected to establish a nomogram. The consistency index for 3-year PFS were 0.88 (95% confidence interval 0.81–0.95) in the training cohort and 0.93 (95% confidence interval 0.87–0.99) in the verification set. The areas under the receiver operating characteristic curve for the 3- and 5-year PFS predictions are 0.891 and 0.842 in the training set; the same conclusion also appeared in the verification set [0.835 (3-year), 0.803(5-year)].ConclusionsThis study established a prognostic nomogram for endometrial cancer that provides a more individualised and accurate estimation of PFS for patients, which will help physicians make follow-up strategies and risk stratification.     

Nomogram to diagnosis of obstructive sleep apnoea-hypopnoea syndrome in high-risk Chinese adult patients

Introduction

Many scales are designed to screen for obstructive sleep apnoea-hypopnoea syndrome (OSAHS); however, there is a lack of an efficiently and easily diagnostic tool, especially for Chinese. Therefore, we conduct a cross-sectional study in China to develop and validate an efficient and simple clinical diagnostic model to help screen patients at risk of OSAHS.

Methods

This study based on 782 high-risk patients (aged >18 years) admitted to the Sleep Medicine department of the Sixth Affiliated Hospital, Sun Yat-sen University from 2015 to 2021. Totally 34 potential predictors were evaluated. We divided all patients into training and validation dataset to develop diagnostic model. The univariable and multivariable logistic regression model were used to build model and nomogram was finally built.

Results

Among 602 high-risk patients with median age of 46 (37, 56) years, 23.26% were women. After selecting using the univariate logistic model, 15 factors were identified. We further used the stepwise method to build the final model with five factors: age, BMI, total bilirubin levels, high Berlin score, and symptom of morning dry mouth or mouth breathing. The AUC was 0.780 (0.711, 0.848), with sensitivity of 0.848 (0.811, 0.885), specificity of 0.629 (0.509, 0.749), accuracy of 0.816 (0.779, 0.853). The discrimination ability had been verified in the validation dataset. Finally, we established a nomogram model base on the above final model.

Conclusion

We developed and validated a predictive model with five easily acquire factors to diagnose OSAHS patient in high-risk population with well discriminant ability. Accordingly, we finally build the nomogram model.