Nomogram

About: Nomogram is a research topic. Over the lifetime, 5429 publications have been published within this topic receiving 86167 citations. The topic is also known as: nomograph & nomograms.

Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer: A multi- institutional update

Abstract: Objective. —To combine the clinical data from 3 academic institutions that serve as centers of excellence for the surgical treatment of clinically localized prostate cancer and develop a multi-institutional model combining serum prostate-specific antigen (PSA) level, clinical stage, and Gleason score to predict pathological stage for men with clinically localized prostate cancer. Design. —In this update, we have combined clinical and pathological data for a group of 4133 men treated by several surgeons from 3 major academic urologic centers within the United States. Multinomial log-linear regression was performed for the simultaneous prediction of organ-confined disease, isolated capsular penetration, seminal vesicle involvement, or pelvic lymph node involvement. Bootstrap estimates of the predicted probabilities were used to develop nomograms to predict pathological stage. Additional bootstrap analyses were then obtained to validate the performance of the nomograms. Patients and Settings. —A total of 4133 men who had undergone radical retropubic prostatectomy for clinically localized prostate cancer at The Johns Hopkins Hospital (n=3116), Baylor College of Medicine (n=782), and the University of Michigan School of Medicine (n=235) were enrolled into this study. None of the patients had received preoperative hormonal or radiation therapy. Outcome Measures. —Simultaneous prediction of organ-confined disease, isolated capsular penetration, seminal vesicle involvement, or pelvic lymph node involvement using updated nomograms. Results. —Prostate-specific antigen level, TNM clinical stage, and Gleason score contributed significantly to the prediction of pathological stage ( P Conclusions. —The data represent a multi-institutional modeling and validation of the clinical utility of combining PSA level measurement, clinical stage, and Gleason score to predict pathological stage for a group of men with localized prostate cancer. Clinicians can use these nomograms when counseling individual patients regarding the probability of their tumor being a specific pathological stage; this will enable patients and physicians to make more informed treatment decisions based on the probability of a pathological stage, as well as risk tolerance and the values they place on various potential outcomes.

Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer

Abstract: PurposeTo develop and validate a radiomics nomogram for preoperative prediction of lymph node (LN) metastasis in patients with colorectal cancer (CRC).Patients and MethodsThe prediction model was developed in a primary cohort that consisted of 326 patients with clinicopathologically confirmed CRC, and data was gathered from January 2007 to April 2010. Radiomic features were extracted from portal venous–phase computed tomography (CT) of CRC. Lasso regression model was used for data dimension reduction, feature selection, and radiomics signature building. Multivariable logistic regression analysis was used to develop the predicting model, we incorporated the radiomics signature, CT-reported LN status, and independent clinicopathologic risk factors, and this was presented with a radiomics nomogram. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Internal validation was assessed. An independent validation cohort contained 200 consecutive p...

A Preoperative Nomogram for Disease Recurrence Following Radical Prostatectomy for Prostate Cancer

Abstract: Background: Few published studies have combined clinical prognostic factors into risk profiles that can be used to predict the likelihood of recurrence or metastatic progression in patients following treatment of prostate cancer. We developed a nomogram that allows prediction of disease recurrence through use of preoperative clinical factors for patients with clinically localized prostate cancer who are candidates for treatment with a radical prostatectomy. Methods: By use of Cox proportional hazards regression analysis, we modeled the clinical data and disease follow-up for 983 men with clinically localized prostate cancer whom we intended to treat with a radical prostatectomy. Clinical data included pretreatment serum prostate-specific antigen levels, biopsy Gleason scores, and clinical stage. Treatment failure was recorded when there was clinical evidence of disease recurrence, a rising serum prostate-specific antigen level (two measurements of 0.4 ng/mL or greater and rising), or initiation of adjuvant therapy. Validation was performed on a separate sample of 168 men, also from our institution. Results: Treatment failure (i.e., cancer recurrence) was noted in 196 of the 983 men, and the patients without failure had a median follow-up of 30 months (range, 1-146 months). The 5-year probability of freedom from failure for the cohort was 73% (95% confidence interval = 69%-76%). The predictions from the nomogram appeared accurate and discriminating, with a validation sample area under the receiver operating characteristic curve (i.e., comparison of the predicted probability with the actual outcome) of 0.79. Conclusions: A nomogram has been developed that can be used to predict the 5-year probability of treatment failure among men with clinically localized prostate cancer treated with radical prostatectomy.

Predicting the Outcome of Salvage Radiation Therapy for Recurrent Prostate Cancer After Radical Prostatectomy

Abstract: Purpose An increasing serum prostate-specific antigen (PSA) level is the initial sign of recurrent prostate cancer among patients treated with radical prostatectomy. Salvage radiation therapy (SRT) may eradicate locally recurrent cancer, but studies to distinguish local from systemic recurrence lack adequate sensitivity and specificity. We developed a nomogram to predict the probability of cancer control at 6 years after SRT for PSA-defined recurrence. Patients and Methods Using multivariable Cox regression analysis, we constructed a model to predict the probability of disease progression after SRT in a multi-institutional cohort of 1,540 patients. Results The 6-year progression-free probability was 32% (95% CI, 28% to 35%) overall. Forty-eight percent (95% CI, 40% to 56%) of patients treated with SRT alone at PSA levels of 0.50 ng/mL or lower were disease free at 6 years, including 41% (95% CI, 31% to 51%) who also had a PSA doubling time of 10 months or less or poorly differentiated (Gleason grade 8 to 10) cancer. Significant variables in the model were PSA level before SRT (P .001), prostatectomy Gleason grade (P .001), PSA doubling time (P .001), surgical margins (P .001), androgen-deprivation therapy before or during SRT (P .001), and lymph node metastasis (P .019). The resultant nomogram was internally validated and had a concordance index of 0.69. Conclusion Nearly half of patients with recurrent prostate cancer after radical prostatectomy have a long-term PSA response to SRT when treatment is administered at the earliest sign of recurrence. The nomogram we developed predicts the outcome of SRT and should prove valuable for medical decision making for patients with a rising PSA level. J Clin Oncol 25:2035-2041. © 2007 by American Society of Clinical Oncology