Pre-treatment nomogram for disease-specific survival of patients with chemotherapy-naive androgen independent prostate cancer

OBJECTIVE: Our objective was to develop a nomogram that predicts the probability of cancer-specific survival in men with untreated androgen-independent prostate cancer (AIPC). METHODS: AIPC was diagnosed in 129 consecutive patients between 1989 and 2002. No patient received cytotoxic chemotherapy. Univariate and multivariate Cox regression models were used to test the association between prostate-specific antigen (PSA) level at initiation of androgen deprivation, PSA doubling time (PSADT), PSA nadir on androgen deprivation therapy (ADT), time from ADT to AIPC, and AIPC-specific mortality. Multivariate regression coefficients were then used to develop a nomogram predicting AIPC-specific survival at 12-60 mo after AIPC diagnosis. Two-hundred bootstrap resamples were used to internally validate the nomogram. RESULTS: AIPC-specific mortality was recorded in 74 of 129 patients (57.4%). Other-cause mortality was recorded in 7 men (5.4%). Median overall survival was 52.0 mo (mean, 36.0 mo) and median AIPC-specific survival was 54.0 mo (mean, 35.0 mo). In univariate regression models, all variables were significant predictors of AIPC-specific survival (p < or = 0.02). In multivariate models, PSADT and time from androgen deprivation to AIPC remained statistically significant (p < or = 0.004). Bootstrap-corrected predictive accuracy of the nomogram was 80.9% versus 74.9% for our previous model. CONCLUSIONS: A nomogram predicting AIPC-specific survival is between 13% and 14% more accurate than previous nomograms and 6% more accurate than tree regression-based predictions obtained from the same data. Moreover, a nomogram approach combines several advantages, such as user-friendly interface and precise estimation of individual recurrence probability at several time points after AIPC diagnosis, which all patients deserve to know and all treating physicians need to know.     

Evaluation of Preoperative Therapy for Pancreatic Cancer Using a Prognostic Nomogram

Background Theoretical benefits of preoperative chemoradiation therapy (preop CRT) for pancreatic cancer include improved efficacy, resectability, and patient selection. The goal of this study was to evaluate the applicability of a nomogram, which was developed for patients undergoing resection without preop CRT and which incorporates several post-resection pathological factors, to a population of patients who received preop CRT prior to resection.Methods From 1994 to 2004, 82 patients with biopsy-proven, radiographically localized adenocarcinoma of the pancreatic head underwent preop CRT followed by pancreaticoduodenectomy (PD); 50 concurrent patients underwent PD without preop CRT. Mean nomogram-predicted disease-specific survival (DSS) rates were compared with observed DSS rates from the time of resection.Results Despite having more locally advanced tumors on initial staging (21 vs. 8%; P < .05), patients who received preop CRT had smaller resected tumors (mean 2.3 vs. 3.1 cm; P < .01), were less likely to have T3 tumors (54 vs. 80%, P < .01), were less likely to have positive lymph nodes (29 vs. 58%, P < .01), and had fewer positive lymph nodes (mean .4 vs. 1.9, P < .01), all factors that imply treatment effect and favorably impact on nomogram-predicted DSS. Observed DSS was similar to predicted DSS in both groups.Conclusions The similarity in observed and predicted DSS following resection in patients who received preop CRT suggests that the effects of preop CRT—whether treatment, selection, or no effect—are reflected by the nomogram. The ability of the nomogram to evaluate the effects of preop CRT on survival is limited by the potential effects of preop CRT on factors within the nomogram.     

Prediction of progression-free survival rates after bevacizumab plus interferon versus interferon alone in patients with metastatic renal cell carcinoma: comparison of a nomogram to the Motzer criteria

Background

The combination of bevacizumab plus interferon (BEV + IFN) for treatment of metastatic renal cell carcinoma (mRCC) is associated with improved progression-free survival (PFS) in a phase 3 study.

Objective

To develop a novel model for prediction of individual PFS using data from the randomized, controlled phase 3 trial of BEV + IFN or interferon alone. The ability of the Motzer criteria for prediction of PFS was also assessed.

Design, setting, and participants

Pretreatment parameters of 628 patients were included in the Cox regression model predicting PFS at 6, 12, 18, and 24 mo. BEV + IFN was administered to 337 patients; 291 patients received interferon alone. The developed model and the Motzer criteria were internally validated using Harrell's concordance index and calibrated.

Results and limitations

Median PFS was 10.2 versus 4.6 mo (p < 0.001) for patients receiving BEV + IFN or interferon alone, respectively. The novel model relying on age, Karnofsky performance status, baseline albumin, alkaline phosphatase, and time from primary diagnosis to treatment resulted in the highest discrimination (area under the curve [AUC]: 72.8, 75.0, 72.8, and 70.8% at 6, 12, 18, and 24 mo). The AUC of the Motzer criteria risk groups was 63.7, 61.8, 58.6, and 51.8% for the same time points. Comparison of discriminatory ability between the developed model and the Motzer criteria showed statistically significant differences (all p ≤ 0.02). An external validation of the new model is warranted.

Conclusions

The developed model identified prognostic factors of PFS in mRCC patients treated with BEV + IFN or interferon alone and quantified individual risk of PFS. Relative to the Motzer criteria, the novel model demonstrated better discriminatory properties. The model may serve clinicians in identifying patients who can benefit the most from BEV + IFN versus interferon alone.     

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.     

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.     

An Internally Validated Nomogram for Predicting the Likelihood of Improvement of Clinical Global Impression in Patients With Lifelong Premature Ejaculation Treated With Dapoxetine

BackgroundAlthough the introduction of dapoxetine has ushered in a new era in the treatment of premature ejaculation, many patients with lifelong premature ejaculation (LPE) exhibit an unimproved clinical global impression even after treatment with dapoxetine.AimTo investigate independent predictors of the improvement of Clinical Global Impression (iCGI) in patients with LPE treated with dapoxetine and develop a nomogram to predict a patient's likelihood of achieving iCGI.MethodsData of 243 patients with LPE diagnosed at Xijing Hospital (Xi'an, China) and Northwest Women's and Children's Hospital (Xi'an, China) from January 2019 to May 2020 were analyzed. Independent predictors of iCGI were identified, and a nomogram was developed using R software based on a multivariate logistic regression model. The predictive accuracy of the nomogram was measured using the area under the receiver operating characteristic curve. The nomogram was calibrated by comparing predictions with observations.Main Outcome MeasuresThe primary outcome was the patient-rated Clinical Global Impression of Change scale score after a 4-week course of dapoxetine treatment, which was collected via an online questionnaire. A Clinical Global Impression of Change score of ≥1 was defined as iCGI in this study.ResultsPatients with LPE with at least a bachelor's degree, a self-reported intravaginal ejaculation latency time of >1 minute, and an International Index of Erectile Function question 5 score of ≥3 were independent factors associated with achieving iCGI, whereas a Premature Ejaculation Diagnostic Tool question 1 score of ≥2 was an independent factor negatively associated with achieving iCGI. The predictive accuracy of the nomogram, which was developed by integrating all variables with independent predictive significance, was 0.710 (95% confidence interval: 0.702–0.718). In addition, the calibration plot demonstrated excellent agreement between predictions and observations.Clinical ImplicationsIf the predictive performance of our nomogram is further proven in multiple external validations, it can be used to select suitable patients for dapoxetine treatment, thereby reducing the number of patients discontinuing treatment.Strengths & LimitationsThis study developed the first nomogram for predicting the likelihood of achieving iCGI in patients with LPE treated with dapoxetine. However, our nomogram was not externally validated using independent cohorts from other institutions.ConclusionThis study identified several independent predictors of iCGI in patients with LPE treated with dapoxetine. An effective nomogram was developed to predict their likelihood of achieving iCGI. External validations using data of Western patients with LPE are required to test the broader applicability of this Chinese patient-based tool.Hou G, Gao M, Zhang L, et al. An Internally Validated Nomogram for Predicting the Likelihood of Improvement of Clinical Global Impression in Patients With Lifelong Premature Ejaculation Treated With Dapoxetine. J Sex Med 2020;17:2341–2350.     

A novel prognostic nomogram based on microvascular invasion and hematological biomarkers to predict survival outcome for hepatocellular carcinoma patients

PurposeThis study aimed to develop and validate a nomogram for overall survival (OS) prediction in which combine clinical characteristics and hematological biomarkers in patients with hepatocellular carcinoma (HCC).MethodsWe performed a retrospective analysis of 807 HCC patients. All the clinical data of these patients were collected through electronic medical record (EMR). The independent predictive variables were identified by cox regression analysis. We tested the accuracy of the nomograms by discrimination and calibration, and then plotted decision curves to assess the benefits of nomogram-assisted decisions in a clinical context, and compared with the TNM staging systems and microvascular invasion (MVI) on HCC prognosis.ResultsThe primary cohort consisted of 545 patients with clinicopathologically diagnosed with HCC from 2008 to 2013, while 262 patients from 2014 to 2016 in external validation cohort. Variables included in the nomograms were TNM Stage, microvascular invasion (MVI), alpha fetoprotein (AFP), platelet to lymphocyte ratio (PLR) and prothrombin time (PT). The C-index of nomogram was 0.768, which was superior than the C-index of TNM Stage (0.660, P < 0.001) and MVI(0.664, P < 0.001) alone in the primary cohort. In the validation cohort, the models had a C-index of 0.845, and were also statistically higher when compared to C-index values for TNM Stage (0.687, P < 0.001) and MVI(0.684, P < 0.001). Calibration curves showed adequate calibration of predicted and reported OS prediction throughout the range of HCC outcomes. Decision curve analysis demonstrated that the nomogram was clinically useful than the TNM Stage and MVI alone. Moreover, patients were divided into three distinct risk groups for OS by the nomogram: low risk group, middle risk group and a high risk group, respectively.ConclusionThe nomogram presents more accurate and useful prognostic power, which could be used to predict OS for patients with HCC.     

Prognostic value of an inflammatory biomarker-based clinical algorithm in septic patients in the emergency department: An observational study

BackgroundTo develop an inflammatory biomarker-based, simple-to-use nomogram for the early identification of septic patients at high risk of mortality in the emergency department (ED).MethodsAll patients diagnosed with sepsis admitted to the intensive care unit (ICU) from the ED were screened from the Medical Information Mart for Intensive Care III database and divided into two cohorts: the primary cohort and the validation cohort. We used bivariate logistic regression analysis to determine independent risk factors and to construct a predictive nomogram and subsequently evaluated the calibration, discrimination and clinical usefulness of the nomogram. The gradient boosting machine (GBM) model was used to more accurately evaluate these variables.ResultsA total of 5663 admissions were enrolled, of which 3964 comprised the primary cohort and 1699 comprised the validation group, with 28-day mortality rates of 21.2% and 20.4%, respectively. Age > 69, neutrophil-to-lymphocyte ratio (NLR) > 9.8, platelet-to-lymphocyte ratio (PLR) > 249.89, lymphocyte-to-monocyte ratio (LMR) ≤ 2.18, and red cell distribution width (RDW) were detected as important determinants of 28-day mortality and included in the nomogram. The calibration plot revealed an adequate fit of the nomogram for predicting the risk of 28-day mortality. Regarding discriminative ability, receiver operating characteristic curve analysis showed that the nomogram had an area under the curve (AUC) of 0.826 (95% CI: 0.811–0.841, P < 0.001) in the primary cohort, which was greater than that of all individual parameters and other scores. Decision curve analysis also indicated that our nomogram was feasible in clinical practice, as the threshold probabilities were 0–0.62 for the primary cohort. The GBM model yielded a significantly greater AUC of up to 0.867.ConclusionsThis proposed simple-to-use nomogram based on age, NLR, PLR, LMR and RDW provides a relatively accurate mortality prediction for septic patients in the ED.     

Development and validation of a nomogram for predicting survival of advanced breast cancer patients in China

BackgroundThere is a lack of prognostic models predicting the overall survival (OS) of advanced breast cancer (ABC) patients in China.MethodsData from the China National Cancer Center database that recorded 4039 patients diagnosed with breast cancer between 1987 and 2019 were extracted and a total of 2263 ABC participants were enrolled in this study, which were further randomized 3:1 and divided into training (n = 1706) and validation (n = 557) groups. The nomogram was built based on independent predictors identified by univariate and multivariate cox regression analyses. The discriminatory and predictive capacities of the nomogram were assessed by Harrell’s concordance index (C-index) and calibration plots.ResultsUnivariate and multivariate analyses found that age, Eastern Cooperative Oncology Group (ECOG) score, T-stage, N-stage, tumor subtype, the presence of distant lymph node (DLN)/liver/brain metastasis, local therapy, efficacy of first-line therapy and metastatic-free interval (MFI) were significantly related to OS (all P < 0.05). These variables were incorporated into a nomogram to predict the 2-year and 3-year OS of ABC patients. The C-indexes of the nomogram were 0.700 (95% confidence interval [CI]: 0.683–0.717) for the training set and 0.686 (95% CI: 0.652–0.719) for the validation set. The calibration curves revealed satisfactory consistency between actual survival and nomogram prediction in both the internal and external validations. The nomogram was capable of stratifying patients into different risk cohorts.ConclusionsWe constructed and validated a nomogram that might serve as an efficient tool to provide prognostic prediction for ABC patients and guide the physicians to make personalized treatment decisions.