A Nomogram Based on the Log Odds of Positive Lymph Nodes Predicts the Prognosis of Patients With Distal Cholangiocarcinoma After Surgery

Prediction of survival after pancreatoduodenectomy for distal cholangiocarcinoma: independent external validation of a prognostic model for 3-year overall survival in Sweden

OBJECTIVES

The only treatment with curative potential for distal cholangiocarcinoma (dCCA) is radical surgery which can be complemented with adjuvant chemotherapy. The aim of the present study was to perform an independent external validation of a prognostic model for 3-year overall survival based on routine clinicopathological variables for patients treated with pancreatoduodenectomy for dCCA.

MATERIALS AND METHODS

All patients with a histopathological confirmed dCCA that underwent pancreatoduodenectomy in Sweden from 2009 through 2019 were identified in the Swedish National Registry for Pancreatic and Periampullary Cancer. Model performance was estimated using the C-index and calibration plots.

RESULTS

In total 220 patients were included in the study. The median survival was 33 months (IQR 26-40) and 3-year survival rate 47% (95% CI 40-53%). The prognostic model had a C-index of 0.69 (95% CI 0.62-0.72). Calibration plots revealed overestimated risk of death across risk groups in the full cohort. Calibration was good in the subgroup of patients that did not receive adjuvant treatment.

CONCLUSIONS

The prognostic model showed reasonable discriminative ability but some miscalibration likely since the effect of adjuvant treatment is not included in the model. Given that the model was developed in cohorts treated prior to the current adjuvant standard of care the model can be used to estimate baseline risk prior to risk/benefit decision for adjuvant treatment as well as stratification for clinical trials but with a risk to underestimate 3-year overall survival for patients that receive adjuvant treatment.

A machine learning predictive model for recurrence of resected distal cholangiocarcinoma: Development and validation of predictive model using artificial intelligence

INTRODUCTION

Distal Cholangiocarcinoma (dCCA) represents a challenge in hepatobiliary oncology, that requires nuanced post-resection prognostic modeling. Conventional staging criteria may oversimplify dCCA complexities, prompting the exploration of novel prognostic factors and methodologies, including machine learning algorithms. This study aims to develop a machine learning predictive model for recurrence after resected dCCA.

MATERIAL AND METHODS

This retrospective multicentric observational study included patients with dCCA from 13 international centers who underwent curative pancreaticoduodenectomy (PD). A LASSO-regularized Cox regression model was used to feature selection, examine the path of the coefficient and create a model to predict recurrence. Internal and external validation and model performance were assessed using the C-index score. Additionally, a web application was developed to enhance the clinical use of the algorithm.

RESULTS

Among 654 patients, LNR (Lymph Node Ratio) 15, neural invasion, N stage, surgical radicality, and differentiation grade emerged as significant predictors of disease-free survival (DFS). The model showed the best discrimination capacity with a C-index value of 0.8 (CI 95 %, 0.77%-0.86 %) and highlighted LNR15 as the most influential factor. Internal and external validations showed the model's robustness and discriminative ability with an Area Under the Curve of 92.4 % (95 % CI, 88.2%-94.4 %) and 91.5 % (95 % CI, 88.4%-93.5 %), respectively. The predictive model is available at https://imim.shinyapps.io/LassoCholangioca/.

CONCLUSIONS

This study pioneers the integration of machine learning into prognostic modeling for dCCA, yielding a robust predictive model for DFS following PD. The tool can provide information to both patients and healthcare providers, enhancing tailored treatments and follow-up.

Different lymph node staging systems for predicting the prognosis of colorectal neuroendocrine neoplasms

BACKGROUND

Colorectal neuroendocrine neoplasms (NENs) are a rare malignancy that primarily arises from the diffuse distribution of neuroendocrine cells in the colon and rectum. Previous studies have pointed out that the status of lymph node may be used to predict the prognosis.

AIM

To investigate the predictive values of lymph node ratio (LNR), positive lymph node (PLN), and log odds of PLNs (LODDS) staging systems on the prognosis of colorectal NENs treated surgically, and compare their predictive values.

METHODS

This cohort study included 895 patients with colorectal NENs treated surgically from the Surveillance, Epidemiology, and End Results database. The endpoint was mortality of patients with colorectal NENs treated surgically. X-tile software was utilized to identify most suitable thresholds for categorizing the LNR, PLN, and LODDS. Participants were selected in a random manner to form training and testing sets. The prognosis of surgically treating colorectal NENs was examined using multivariate cox analysis to assess the associations of LNR, PLN, and LODDS with the prognosis of colorectal NENs. C-index was used for assessing the predictive effectiveness. We conducted a subgroup analysis to explore the different lymph node staging systems' predictive values.

RESULTS

After adjusting all confounding factors, PLN, LNR and LODDS staging systems were linked with mortality in patients with colorectal NENs treated surgically (P < 0.05). We found that LODDS staging had a higher prognostic value for patients with colorectal NENs treated surgically than PLN and LNR staging systems. Similar results were obtained in the different G staging subgroup analyses. Furthermore, the area under the receiver operating characteristic curve values for LODDS staging system remained consistently higher than those of PLN or LNR, even at the 1-, 2-, 3-, 4-, 5- and 6-year follow-up periods.

CONCLUSION

LNR, PLN, and LODDS were found to significantly predict the prognosis of patients with colorectal NENs treated surgically.

Log odds of positive lymph nodes (LODDS)-based novel nomogram for survival estimation in patients with invasive micropapillary carcinoma of the breast

BACKGROUND

Invasive micropapillary carcinoma (IMPC) of the breast is known for its high propensity for lymph node (LN) invasion. Inadequate LN dissection may compromise the precision of prognostic assessments. This study introduces a log odds of positive lymph nodes (LODDS) method to address this issue and develops a novel LODDS-based nomogram to provide accurate prognostic information.

METHODS

The study analyzed data from 1,901 patients with breast IMPC from the Surveillance, Epidemiology, and End Results database. It assessed the relationships between LODDS and the number of excised LN (eLN), positive LN (pLN), and the pLN ratio (pLNR), identifying an optimal threshold value using a restricted cubic spline method. Predictive factors were identified by the Cox least absolute shrinkage and selection operator (Cox-LASSO) regression and validated through multivariate Cox regression to construct a nomogram. The model's accuracy, discrimination, and utility were assessed. The study also explored the consequences of excluding LODDS from the nomogram and compared its effectiveness with the tumor-node-metastasis (TNM) staging system.

RESULTS

LODDS improved N status classification by identifying heterogeneity in patients with pLN ratios of 0% (pLN =0) or 100% (pLN =eLN) and setting -1.08 as the ideal cutoff. Five independent prognostic factors for breast cancer-specific survival (BCSS) were identified: tumor size, N status, LODDS, progesterone receptor status, and histological grade. The LODDS-based nomogram achieved a strong concordance index of 0.802 (95% CI: 0.741-0.863), surpassing both the version without LODDS and the conventional TNM staging in all tests.

CONCLUSIONS

For breast IMPC, LODDS served as an independent prognostic factor, its effectiveness unaffected by the anatomical LN count, enhancing the accuracy of N staging. The LODDS-based nomogram showed promise in offering more personalized prognostic information.

Subserosal Layer and/or Pancreatic Invasion Based on Anatomical Features as a Novel Prognostic Indicator in Patients with Distal Cholangiocarcinoma

The American Joint Committee on Cancer (AJCC) 8th edition T-staging system for distal cholangiocarcinoma (DCC) proposes classification according to the depth of invasion (DOI); nevertheless, DOI measurement is complex and irreproducible. This study focused on the fibromuscular layer and evaluated whether the presence or absence of penetrating fibromuscular invasion of DCC contributes to recurrence and prognosis. In total, 55 patients pathologically diagnosed with DCC who underwent surgical resection from 2002 to 2022 were clinicopathologically examined. Subserosal layer and/or pancreatic (SS/Panc) invasion, defined as penetration of the fibromuscular layer and invasion of the subserosal layer or pancreas by the cancer, was assessed with other clinicopathological prognostic factors to investigate recurrence and prognostic factors. According to the AJCC 8th edition, there were 11 T1, 28 T2, and 16 T3 cases, with 44 (80%) cases of SS/Panc invasion. The DOI was not significantly different for both recurrence and prognostic factors. In the multivariate analysis, only SS/Panc was identified as an independent factor for prognosis (hazard ratio: 16.1; 95% confidence interval: 2.1-118.8, p = 0.006). In conclusion, while the determination of DOI in DCC does not accurately reflect recurrence and prognosis, the presence of SS/Panc invasion may contribute to the T-staging system.

Establishment and validation of a nomogram to predict the neck contracture after skin grafting in burn patients: A multicentre cohort study

Cervical burn contracture is one of the burn contractures with the highest incidence and severity, and there is no effective method to predict the risk of neck contracture. This study aimed to investigate the effect of combined cervicothoracic skin grafting on the risk of neck contracture in burn patients and to develop a nomogram to predict the risk of neck contracture after skin grafting in burn patients. Data from 212 patients with burns who underwent neck skin grafting were collected from three hospitals, and the patients were randomly divided into training and validation sets. Independent predictors were identified through univariate and multivariate logistic regression analyses and incorporated into a prognostic nomogram. Its performance was assessed using the receiver operating characteristic area under the curve, calibration curve, and decision curve analysis. Burn depth, combined cervicothoracic skin grafting, graft thickness, and neck graft size were significantly associated with neck contractures. In the training cohort, the nomogram had an area under the curve of 0.894. The calibration curve and decision curve analysis indicated good clinical applicability of the nomogram. The results were tested using a validation dataset. Combined cervicothoracic skin grafting is an independent risk factor for neck contracture. Our nomogram demonstrated excellent performance in predicting neck contracture risk.

Predictors, Patterns, and Impact of Adequate Lymphadenectomy in Intrahepatic Cholangiocarcinoma

INTRODUCTION

Despite lymph node metastases (LNMs) being associated with worse survival, adequate lymph node evaluation (LNE) has not been universally adopted for intrahepatic cholangiocarcinoma (ICC). We sought to evaluate trends in LNE, predictors of LNE and LNM, as well as the role of adequate lymphadenectomy in stratifying patients relative to survival.

METHODS

Patients who underwent curative-intent liver resection for ICC (2010-2019) were identified from the National Cancer Database and stratified according to LNE: 0, 1-5 (inadequate lymphadenectomy) and ≥6 (adequate lymphadenectomy). Multivariate logistic regression was utilized to assess predictors of LNE and LNM. Overall survival and receipt of adequate lymphadenectomy were assessed relative to LNM and log-odds of lymph nodes (LODDS).

RESULTS

Among 6507 patients, adequate lymphadenectomy was performed in only 1118 (17.2%) patients, although compliance with adequate lymphadenectomy increased over time (2010-2012: 14.2% vs. 2016-2019: 18.9%; p < 0.001). After controlling for relevant factors, region (reference: Northeast; Midwest: odds ratio [OR] 1.90, 95% confidence interval [CI] 1.48-2.44; South: OR 1.64, 95% CI 1.28-2.10; West: OR 1.83, 95% CI 1.37-2.44) and preoperative nodal status (reference: cN0; cNx: OR 2.18, 95% CI 1.68-2.95; cN1: OR 3.88, 95% CI 3.02-4.98) strongly predicted adequate lymphadenectomy. Furthermore, adequate lymphadenectomy resulted in higher odds of detecting ≥1 LNMs (OR 2.63, 95% CI 2.25-3.08), regardless of preoperative nodal status. Adequate lymphadenectomy demonstrated an improved ability to stratify patients relative to 5-year survival based on LNM (N0: 51.3% vs. N1: 30.6% vs. N2: 13.7%; p < 0.001) and LODDS (LODDS1: 50.7% vs. LODDS2: 27.4% vs. LODDS3: 15.7%; p < 0.001).

CONCLUSIONS

Compliance with adequate lymphadenectomy at the time of surgery for ICC remains suboptimal with marked regional variations. Adequate lymphadenectomy was associated with higher odds of detecting LNM and improved survival stratification relative to both LNM and LODDS. Greater emphasis on nodal evaluation is required to ensure optimal management of ICC.

Comparing the predictive performance of different lymph node staging systems for postoperative overall survival in patients with ampullary carcinoma

Aim

This study was to analyze and compare the predictive performance of the 7th and the 8th edition American Joint Committee on Cancer (AJCC) N staging system, lymph nodes ratio (LNR) and log odds of positive lymph node (LODDS) for the survival of patients with ampullary carcinomas (ACs).

Method

This retrospective cohort study included patients with primary ACs after surgery from the Surveillance, Epidemiology, and End Results (SEER) 2004-2015. Univariate and multivariate Cox proportional hazard models were used. The study population was divided into a training set and a testing set in a ratio of 7-3. The C-index and area under the curve (AUC) were used to compare the predictive performance of the four staging on overall survival (OS) in the training set and the testing set.

Results

A total of 7,480 patients with primary ACs (1,178 survived and 1,128 dead) were in this study. The average follow-up time was 41.1 months. N1 stage and N2 stage of the 8th edition AJCC N staging system, LNR staging (0-0.3), LNR (>0.3), LODDS (-2.4 to -0.8) and LODDS (>-0.8) were associated with OS in AC patients after adjusting for age, race, pT stage, tumor size, grade, radiation, and insurance. The C-index of the 7th AJCC N staging was significantly lower than the C-index of the 8th AJCC N staging in the training set [0.608 vs. 0.629, P < 0.001] and testing set [0.635 vs. 0.658, P < 0.001]. The C-index of the LODDS staging was significantly higher than the C-index of the 8th AJCC N staging in the training set [0.641 vs. 0.629, P = 0.034] and testing set [0.671 vs. 0.658, P = 0.034]. LODDS staging may be a potential predictor of OS at 6 months [AUC = 0.687], 12 months (AUC = 0.692), and 48 months (AUC = 0.709), and LNR staging (AUC = 0.655) may be a potential predictor of OS at 24 months in AC patients. The predictive ability of LNR staging and LODDS staging were also found in different subgroups.

Conclusion

The LNR and LODDS staging systems' predictive performance for OS of AC patients were superior to the 8th edition AJCC N staging system, especially in patients ages ≥65 or with higher tumor grade (grade II and III). The LNR staging and the LODDS staging were potential predictors for 24-month OS, and 6, 12, 24 and 48-month OS, respectively.

Lymph Node Ratio Nomogram-Based Prognostic Model for Resected Distal Cholangiocarcinoma

BACKGROUND

Several variables have been described as prognostic factors for resected distal cholangiocarcinoma (dCC), including lymph node metastases (N status) and lymph node ratio (LNR). The present study aimed to evaluate the prognostic value of LNR on survival and to establish a novel prognostic nomogram to predict the cancer-specific recurrence-free survival (RFS) of dCC.

STUDY DESIGN

Between December 2006 and September 2020, 415 consecutive patients who underwent pancreaticoduodenectomy (PD) for dCC in 10 centers were identified. Multivariate Cox analysis was used to identify all independent risk factors among several prognostic factors. A nomogram was then developed and assessed by integrating the independent prognostic factors into the model, and the concordance index (C-index) was used to evaluate its performance.

RESULTS

According to Cox regression multivariate analysis, a nomogram based on independent prognostic factor for RFS was performed including LNR 15 (hazard ratio [HR] 2.442, 95% CI 1.348-4.425, p = 0.003), perineural invasion (HR 3.100, 95% CI 1.183-8.122, p = 0.025), differentiation grade (HR 2.100, 95% CI 1.172-4.143, p = 0.021), and radicality of PD (HR 2.276, 95% CI 1.223-4.234, p = 0.009). The C-index of the nomogram, tailored based on the previous significant factors, was 0.8.

CONCLUSIONS

LNR15 yields a high prognostic efficiency for RFS. The nomogram based on LNR can provide an accurate prognosis assessment for patients with resected dCC.

A Prognostic Nomogram Based on Log Odds of Positive Lymph Nodes to Predict Overall Survival for Non-Metastatic Bladder Cancer Patients after Radical Cystectomy

(1) Purpose: The purpose of this study was to evaluate the prognostic capacity of the pathological N status (pN), lymph node ratio (LNR), and the log odds of positive lymph nodes (LODDS), and to build a prognostic nomogram to predict overall survival (OS) for bladder cancer patients treated by radical cystectomy. (2) Methods: The clinical and pathological characteristics of 10,938 patients with bladder cancer were identified from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017. The predictive capacity was assessed by univariate and multivariate Cox regression analyses, the area under the receiver operating characteristic curve (AUC), and C-index. Calibration curves, decision curve analysis (DCA), and risk-grouping were utilized to evaluate the predictive accuracy and discriminative ability of the nomogram. (3) Results: LODDS was an independent risk factor for bladder cancer (all p < 0.001) and demonstrated the highest values of C-index and AUC. The values of AUCs in the training cohort were 0.747, 0.743, and 0.735 for predicting 1-, 3-, and 5-year OS, respectively. Calibration curves and DCA curves suggested the excellent clinical application value of our nomogram. (4) Conclusions: LODDS is a better predictive indicator for bladder cancer patients compared to pN and LNR. The LODDS-incorporated nomogram has excellent accuracy and promising clinical application value for non-metastatic bladder cancer after radical cystectomy.