A Clinical Nomogram for Predicting Node-positive Disease in Esophageal Cancer

Abstract

Objective:We developed and validated a nomogram predicting the likelihood of occult lymph node metastases in surgically resectable esophageal cancers.Background:Patients with esophageal cancer with positive lymph nodes benefit from neoadjuvant therapy, but limitations in current clinical staging techniques mean nodal metastases often go undetected preoperatively.Methods:The National Cancer Database was queried for patients with clinical T1-3N0M0 cancer undergoing upfront esophagectomy from 2004 to 2014. Multivariable logistic regression was used to develop the risk model using both statistical significance and clinical importance criteria for variable selection. Predictive accuracy was assessed and bootstrapping was used for validation. A nomogram was constructed for presentation of the final model.Results:Of 3186 patients, 688 (22%) had pathologic lymph node involvement (pN+) and 2498 (78%) had pN0 status. Variables associated with pN+ status included histology [adenocarcinoma vs squamous: odds ratio (OR) 1.75], tumor stage (T1: reference, T2: OR 1.90, T3: OR 2.17), tumor size (<1 cm: reference, 1–2 cm: OR 2.25, 2–3 cm: OR 3.82, 3–4 cm: OR 5.40, 4–5 cm: OR 5.66, ≥5 cm: OR 6.02), grade (1: reference, 2: OR 2.62, 3: OR 4.39, 4: OR 4.15, X: OR 1.87), and presence of lymphovascular invasion (absent: reference, present: OR 4.70, missing: OR 1.87), all P < 0.001. A nomogram with these variables had good predictive accuracy (Brier score: 0.14, calibration slope: 0.97, c-index: 0.77).Conclusions:We created a nomogram predicting the likelihood of pathologic lymph node involvement in patients with esophageal cancer who are clinically node negative using a generalizable dataset. Risk stratification with this nomogram could improve delivery of appropriate perioperative care.

A Nomogram to Predict Lymph Node Metastasis Risk for Early&nbsp;Esophageal Squamous Cell Carcinoma

“…Thus far, a few researchers have developed nomogram models to predict the risk of LNM in esophageal cancer [6,11,[24][25][26]. For example, Zheng et al [11] recently developed a nomogram for the prediction of LNM in early-stage ESCC patients.…”

Postoperative pneumonia in geriatric patients with a hip fracture: incidence, risk factors and a predictive nomogram

“…The main advantages of this study include: rst, a nomogram was built for the prediction for the development of POP, with good accuracy according to the statistical veri cations. As a graphical presentation of predictive model, nomogram has been widely used in the area of oncology [25][26][27][28], with great advantages such as easy operation, convenience and effectiveness. Previously, we have reported the predictive nomogram for the development of postoperative delirium in elderly patients with a hip fracture [29].…”

Upregulated calcium‐binding tyrosine phosphorylation‐regulated protein‐a/b regulates cell proliferation and apoptosis and predicts poor prognosis in hepatocellular carcinoma

“…Kaplan‐Meier survival curves demonstrated that cases with elevated CABYR‐a/b level have much poorer OS and DFS than those with downregulated CABYR‐a/b level and TCGA database provided similar results. Multivariate analysis and prognostic nomograms, especially the latter, play vital role in evaluating the prognostic impact in cancer . Nomograms, graphic representations of complicated mathematical formulas, was broadly applied as prognostic models to analyze an individual's predicted prognosis by incorporating multiple and detailed prognostic parameters .…”

“…Multivariate analysis and prognostic nomograms, especially the latter, play vital role in evaluating the prognostic impact in cancer. 17 Nomograms, graphic representations of complicated mathematical formulas, was broadly applied as prognostic models to analyze an individual's predicted prognosis by incorporating multiple and detailed prognostic parameters. [18][19][20] In the present study, according to the multivariate analysis, CABYR-a/b-based nomograms were created to interpret the predictive role of CABYRa/b.…”