Nomograms for predicting survival outcomes in patients with primary tracheal tumors: a large population-based analysis

Tracheal Tumors: Clinical Practice Guidelines for Palliative Treatment and Follow-Up

A substantial portion of patients with advanced cancer cannot be cured, regardless of the therapeutic methods employed. Hence, rational palliative causal treatment becomes crucial. Representative studies specifically addressing the exclusive palliative treatment of patients diagnosed with tracheal cancers have not been identified. In most studies, patients treated palliatively constituted a subset of the overall evaluated group. A thorough literature review was conducted, focusing on three types of palliative treatment: palliative radiotherapy, palliative surgical procedures, and systemic treatment for advanced disease. This review uniquely fills a significant gap in the existing literature by providing the first comprehensive and updated clinical practice guidelines specifically focused on the palliative treatment of tracheal tumors. The proposed guidelines emphasize the unique clinical challenges and treatment strategies pertinent to palliative care in tracheal tumors, which are not adequately covered in existing guidelines for other thoracic malignancies.

Treatment outcomes of patients with primary tracheal tumors - analysis of a large retrospective series

OBJECTIVE

Primary tracheal tumors are very rare and their management is not definitely established. Due to its rarity, providing patient care in terms of optimal management poses a considerable challenge. The purpose of this study was to investigate treatment outcomes in patients with these rare tumors.

METHODS

We carried out a retrospective analysis of 89 patients with primary tracheal tumors treated at the Maria Sklodowska-Curie National Research Institute of Oncology in Warsaw, Poland, over sixteen years. The study assessed patient demographics, tumor characteristics and treatment. Different treatment options were compared in terms of overall survival, disease-free survival, and progression-free survival.

RESULTS

A total of 89 patients were included in the study. In the group presented, 45 patients underwent primary radical treatment and 44 were qualified for palliative treatment. Surgical resection was performed in 13 patients out of radically treated patients. The 5 year OS rates in the group of patients who underwent radical treatment and in the group of patients who underwent palliative treatment were 45.9% and 2.3%, respectively. In the group of patients who underwent radical surgical treatment, the 5 year OS was 76.9% compared to 35.8% in the group of patients who underwent nonsurgical treatment.

CONCLUSION

A multidisciplinary team should decide treatment options, including in-depth consideration of surgical treatment options.

Clinicopathological characteristics of patients with primary tracheal tumors: Analysis of eighty-nine cases

BACKGROUND

Primary tracheal tumors are very rare and the literature on this subject is limited. The most common histological type of primary tracheal tumors is squamous cell carcinoma (SCC), followed by adenoid cystic carcinoma (ACC). Limited knowledge exists regarding the behavior and outcomes of different histological types of tracheal cancers. The present study aimed to address this gap by assessing the significance of the histological type of primary tracheal tumors based on our own data and to review the literature.

METHODS

We carried out a retrospective analysis of 89 patients with primary tracheal tumors treated at the Maria Sklodowska-Curie National Research Institute of Oncology in Warsaw, Poland, between 2000 and 2016. The study assessed patient demographics, tumor characteristics and treatment, with a focus on SCC, ACC, and other histological types. Different histological types were compared in terms of overall survival, disease-free survival, and progression-free survival.

RESULTS

SCC was the most frequently diagnosed histological type (56.2%), followed by ACC (21.3%). Patients with SCC were typically older (78% over 60 years), predominantly male (66%), and associated with smoking. In contrast, the ACC had a more balanced gender distribution and did not correlate with smoking. ACC displayed a significantly better prognosis, with a median overall survival of 129.4 months, compared with 9.0 months for SCC.

CONCLUSION

Histological type plays a crucial role in the prognosis of primary tracheal tumors. ACC demonstrated a more favorable outcome compared with SCC.

Prognostic factors and constructing a nomogram in tracheal cancer patients treated with surgical intervention: A study based on SEER database

Although surgery is considered the first choice of treatment for patients diagnosed with tracheal cancer, the prediction of overall survival (OS) in patients undergoing surgical intervention is poor. To address this issue, we developed a nomogram that combined a risk classification system to estimate the OS of patients with tracheal cancer who underwent surgical intervention. A total of 525 qualified patients were selected from the surveillance, epidemiology, and end results database between 1975 and 2018 and were randomly divided into training and validation cohorts (7:3). The parameters of independent prognostic ability were determined using Cox regression analysis, and a nomogram was formed. The predictive ability of the nomogram was tested using the area under the curve of receiver operating characteristic curves and calibration curves. Survival curves were assessed between the different risk classification groups using the Kaplan-Meier method. The results indicated that Age, stage, histology, and tumor size were independent prognostic factors and were included in the predictive model. The calibration plots demonstrated good agreement between the nomogram prediction and actual observation for 24- and 36-month OS. The receiver operating characteristic curves suggested that the predictive model had good discrimination ability, with the area under the curves (training group 0.817, 0.785, and 0.801, respectively) and validation group (0.744, 0.794, and 0.822, respectively). Furthermore, the low-risk group had a better prognosis than the high-risk group in the total, training, and validation cohorts (all P < .001). This study established a novel nomogram system to predict OS and identify independent prognostic factors in patients with tracheal cancer who underwent surgical intervention. This model has the potential to assist doctors in making decisions regarding treatment options.

Malignant and Benign Tracheobronchial Neoplasms: Comprehensive Review with Radiologic, Bronchoscopic, and Pathologic Correlation

Tracheobronchial neoplasms are much less common than lung parenchymal neoplasms but can be associated with significant morbidity and mortality. They include a broad differential of both malignant and benign entities, extending far beyond more commonly known pathologic conditions such as squamous cell carcinoma and carcinoid tumor. Airway lesions may be incidental findings at imaging or manifest with symptoms related to airway narrowing or mucosal irritation, invasion of adjacent structures, or distant metastatic disease. While there is considerable overlap in clinical manifestation, imaging features, and bronchoscopic appearances, an awareness of potential distinguishing factors may help narrow the differential diagnosis. The authors review the epidemiology, imaging characteristics, typical anatomic distributions, bronchoscopic appearances, and histopathologic findings of a wide range of neoplastic entities involving the tracheobronchial tree. Malignant neoplasms discussed include squamous cell carcinoma, malignant salivary gland tumors (adenoid cystic carcinoma and mucoepidermoid carcinoma), carcinoid tumor, sarcomas, primary tracheobronchial lymphoma, and inflammatory myofibroblastic tumor. Benign neoplasms discussed include hamartoma, chondroma, lipoma, papilloma, amyloidoma, leiomyoma, neurogenic lesions, and benign salivary gland tumors (pleomorphic adenoma and mucous gland adenoma). Familiarity with the range of potential entities and any distinguishing features should prove valuable to thoracic radiologists, pulmonologists, and cardiothoracic surgeons when encountering the myriad of tracheobronchial neoplasms in clinical practice. Attention is paid to any features that may help render a more specific diagnosis before pathologic confirmation. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Do We Need TNM for Tracheal Cancers? Analysis of a Large Retrospective Series of Tracheal Tumors

Simple Summary

The TNM (tumor, node, metastases) staging system established by the Union for International Cancer Control/American Joint Committee on Cancer is commonly used to select a treatment method for patients with cancers, guide adjuvant therapy after surgery, and predict the prognosis. It is an essential tool for working with cancer patients in everyday medical practice. Currently, the eighth edition of the TNM staging system is used. Primary tracheal tumors are uncommon neoplasms. Probably due to their rarity, neither an AJCC staging system nor other, widely accepted staging system exists for primary tracheal cancers. Only a few studies stated their proposed guidelines for the staging of tracheal neoplasms. The absence of a universally adopted staging system makes it difficult for clinicians to assess tracheal cancers properly. This makes it challenging to conduct analyses and compare the results of published works. A standard classification system would help assess and qualify patients for treatment and, perhaps, establish uniform indications for adjuvant treatment. All this could contribute to an increase in the proportion of patients qualified for radical surgery, which is the preferred treatment method.

Abstract

Due to the low incidence of primary tracheal neoplasms, there is no uniform system for staging of this disease. Our retrospective analysis based on registry data included 89 patients diagnosed with primary tracheal cancer at the National Research Institute of Oncology in Warsaw, Poland, between January 2000 and December 2016. We analyzed demographic, clinical, pathological, therapeutic, and survival data. The staging—for the purpose of our analysis—was performed retrospectively on the basis of imaging results. Tumor (T) category was defined as a disease confined to the trachea or lesion derived from the trachea and spreading to adjacent structures and organs. Node (N) and metastases (M) categories were divided into absence/presence of metastasis in regional lymph nodes and the absence/presence of distant metastasis. Survival analysis was performed depending on the clinical presentation of these features. There was a significant difference in overall survival depending on the T, N, M categories in the entire group. In the group of patients undergoing radical treatment, the T and N categories had a statistically significant impact on overall survival. In the group of patients treated with palliative aim, only the T category had an impact on overall survival. Multivariate analysis showed statistical significance for the T category in patients undergoing radical and those receiving palliative treatment. The assessment of the anatomical extent of lesions may help decide about treatment options and prognosis.

Comprehensive analysis of prognostic value of lymph node classifications in esophageal squamous cell carcinoma: a large real-world multicenter study

Background:

We aim to assess the prognostic ability of three common lymph node–based staging algorithms, namely, the number of positive lymph nodes (pN), the lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) in patients with esophageal squamous cell carcinoma (ESCC).

Methods:

A total of 3902 ESCC patients treated at 10 Chinese institutions between 2003 and 2013 were included, along with 2465 patients from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic ability of the aforementioned algorithms was evaluated using time-dependent receiver operating characteristic (tdROC) curves, R², Harrell’s concordance index (C-index), and the likelihood ratio chi-square score. The primary outcomes included cancer-specific survival (CSS), overall survival (OS), and CSS with a competing risk of death by non-ESCC causes.

Results:

LODDS had better prognostic performance than pN or LNR in both continuous and stratified patterns. In the multicenter cohort, the multivariate analysis showed that the model based on LODDS classification was superior to the others in predictive accuracy and discriminatory capacity. Two nomograms integrating LODDS classification and other clinicopathological risk factors associated with OS as well as cancer-specific mortality were constructed and validated in the SEER database. Finally, a novel TN_LODDS classification which incorporates the LODDS classification was built and categorized patients in to three new stages.

Conclusion:

Among the three lymph node–based staging algorithms, LODDS demonstrated the highest discriminative capacity and prognostic accuracy for ESCC patients. The nomograms and novel TN_LODDS classification based on LODDS classification could serve as precise evaluation tools to assist clinicians in estimating the survival time of individual patients and improving clinical outcomes postoperatively in the future.

Nomogram for the prediction of individualized overall survival of patients diagnosed with small cell esophageal carcinoma

Background

A nomogram was developed for the estimation of individualized overall survival (OS) of patients diagnosed with small cell esophageal carcinoma (SCEC).

Methods

From the SEER dataset, 427 patients diagnosed with SCEC during the period from 2004 to 2015 were selected as training sets. For the establishment of a nomogram capable of estimating the OS possibility of patients diagnosed with SCEC, a group of independent prognostic factors were identified and incorporated. The effectiveness of the nomogram was then both externally and internally verified among 159 patients from Fudan University Shanghai Cancer Center (FUSCC) who were diagnosed with SCEC between 2006 and 2015. The predictive accuracy and discriminative ability of the nomogram were measured by concordance index (C-index). Comparisons between nomogram and the AJCC staging systems (6th and 7th) were performed with calibration plots and area under the curves (AUC) values.

Results

We identified age, gender, primary site, SEER stage, surgery, radiotherapy, and chemotherapy as seven independent risk factors which were then used to set up the nomogram. Calibration curves indicated that the prediction of the nomogram was consistent with real observations for the possibilities of 1-, 3-, and 5-year OS, and applying the nomogram to the cohort for validation led to reproducible results. Moreover, the C-indices and AUC values were higher in the nomogram than those in the AJCC staging system AJCC which is also aimed at the prediction of OS.

Conclusions

This study resulted in the establishment of the first nomogram for the prediction of individualized OS of patients diagnosed with SCEC. The accuracy rate of prediction of this model may be higher than previously established staging systems.

Nomogram to Predict the Overall Survival of Colorectal Cancer Patients: A Multicenter National Study

BACKGROUND

Colorectal cancer (CRC) is the third foremost cause of cancer-related death and the fourth most commonly diagnosed cancer globally. The study aimed to evaluate the survival predictors using the Cox Proportional Hazards (CPH) and established a novel nomogram to predict the Overall Survival (OS) of the CRC patients.

MATERIALS AND METHODS

A historical cohort study, included 1868 patients with CRC, was performed using medical records gathered from Iran's three tertiary colorectal referral centers from 2006 to 2019. Two datasets were considered as train set and one set as the test set. First, the most significant prognostic risk factors on survival were selected using univariable CPH. Then, independent prognostic factors were identified to construct a nomogram using the multivariable CPH regression model. The nomogram performance was assessed by the concordance index (C-index) and the time-dependent area under the ROC curve.

RESULTS

The age of patients, body mass index (BMI), family history, tumor grading, tumor stage, primary site, diabetes history, T stage, N stage, and type of treatment were considered as significant predictors of CRC patients in univariable CPH model (p < 0.2). The multivariable CPH model revealed that BMI, family history, grade and tumor stage were significant (p < 0.05). The C-index in the train data was 0.692 (95% CI, 0.650-0.734), as well as 0.627 (0.670, 0.686) in the test data.

CONCLUSION

We improved a novel nomogram diagram according to factors for predicting OS in CRC patients, which could assist clinical decision-making and prognosis predictions in patients with CRC.

CT diagnosis and prognosis prediction of tracheal adenoid cystic carcinoma

PURPOSE

To evaluate computed tomography (CT) features and establish a predictive model for the clinical diagnosis and prognosis of tracheal adenoid cystic carcinoma (ACC).

METHOD

From January 2010 to December 2018, 82 patients with tracheal tumors, including 46 patients with ACC confirmed by surgery and histopathology, were enrolled in this study. These patients' clinicopathologic information, CT features and survival outcomes were recorded and analyzed. Independent predictors of diagnosis and prognosis of tracheal ACC were determined by both univariate and multivariate analyses.

RESULTS

Compared with tracheal non-ACC patients, univariate analysis showed that ACC patients were more likely to have extensive longitudinal length (p < 0.001) and to appear as annular wall thickening (p = 0.001), transmural growth (p = 0.036), poorly defined border (p = 0.003) and mild enhancement (p = 0.001). Multivariate logistic analysis showed that longitudinal length and enhancement degree were independent predictors of tracheal ACC. The 3-year and 5-year disease-free survival (DFS) were 75.7 % and 64.5 %, respectively. Longitudinal length (≥ 34 mm), transverse length (≥ 20 mm) and transmural growth were associated with poor DFS in univariate analysis. After multivariate adjustment, only transverse length (≥ 20 mm) was an adverse prognostic factor for DFS (hazard ratio = 4.594, 95 % confidence interval = 1.240-17.017; p = 0.022).

CONCLUSIONS

CT longitudinal length and enhancement degree of tumors showed satisfactory discrimination for tracheal ACC. Excessive CT transverse length might be an unfavorable indicator for ACC recurrence and could be helpful for predicting the survival outcomes of ACC at the initial diagnosis.

Radiation treatment for adult rare cancers: Oldest and newest indication

AIM

Aim of this analysis is to review the role of RT in the management of several rare tumors for adult patients.

METHODS

Collection data regarding RT and rare tumors was made by Pubmed.

RESULTS

For mucosal melanomas, RT is prescribed, being associated with lower local recurrence rate. For trachea tumors, RT was used as adjuvant or salvage treatment for unresectable disease. For pNET, RT can be a suitable option for post-surgical or unresectable/borderline. For bronchopulmonary neuroendocrine tumors the role of adjuvant treatments is uncertain. For hepatobiliary and ovarian malignancy, stereotactic body RT (SBRT) is a promising approach. For soft tissue sarcoma, perioperative treatments are indicated, and a growing role of SBRT in oligometastatic disease is recognized. For endocrine tumors, adjuvant RT has demonstrated benefits through reducing recurrence risk.

CONCLUSION

The radiotherapy is a frequent indication in adult rare cancers; thus the role of Radiation Oncologist must not be neglected.

Development and validation of nomogram combining serum biomarker for predicting survival in patients with resected rectal cancer

Purpose: Nomogram is a widely used tool that precisely predicts individualized cancer prognoses. We aimed to develop and validate a reliable nomogram including serum tumor biomarkers to predict individual overall survival (OS) for patients with resected rectal cancer (RC) and compare the predictive value with the American Joint Committee on Cancer (AJCC) stages.

Patients and methods: We analyzed 520 patients who were diagnosed with non-metastatic rectal cancer as training cohort. External validation was performed in a cohort of 11851 patients from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified and integrated to build a nomogram using the Cox proportional hazard regression model. The nomogram was evaluated by Harrell’s concordance index (C-index) and calibration plots in both training and validation cohort.

Results: The calibration curves for probability of 1-, 3-, and 5-year OS in both cohorts showed favorable accordance between the nomogram prediction and the actual observation. The C-indices of the nomograms to predict OS were 0.71 in training cohort and 0.69 in the SEER cohort, which were higher than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (training cohort, 0.71 vs. 0.58, respectively; P-value < 0.001; validation cohort, 0.69 vs. 0.57, respectively; P-value < 0.001).

Conclusion: We developed and validated a novel nomogram based on CEA and other factors for predicting OS in patients with resected RC, which could assist clinical decision making and improvement of prognosis prediction for individual RC patients after surgery.

Survival analysis via nomogram of surgical patients with malignant pleural mesothelioma in the Surveillance, Epidemiology, and End Results database

Background

Malignant pleural mesothelioma (MPM) is a rare but aggressive tumor that originates from the pleura and has a poor prognosis. Eligible patients can benefit from surgery, but their survival is affected by many factors. Therefore, we created a graphic model that could predict the prognosis of surgically treated patients.

Methods

We retrospectively analyzed data from the Surveillance, Epidemiology, and End Results database from 2004 to 2014 to identify the key factors affecting the prognosis of surgically treated MPM patients. On this basis we built a nomogram to predict survival. We then evaluated the performance of the nomogram in a validation cohort.

Results

In a training cohort of 828 cases, independent prognostic factors, including age, gender, histological type, differentiation, N stage, chemotherapy, type of surgery, and lymph node dissection, were identified. We then developed a nomogram to evaluate individual patient survival. In Kaplan–Meier analysis, a higher score in the nomogram was associated with a worse prognosis. We also used a validation cohort consisting of 312 patients to evaluate the performance of the nomogram, which was well calibrated and had good discrimination ability, with concordance indices of 0.715 and 0.656 for the training and validation cohorts, respectively.

Conclusion

This study has improved our understanding of resected MPM and shown that key factors, including age and histological type, are associated with overall survival. The nomogram is a reliable tool that can help clinicians turn individualized prediction into reality and maximize patient benefit by identifying the most beneficial treatment approach.