Nomogram for Predicting the Overall Survival of Adult Patients With Primary Gastrointestinal Diffuse Large B Cell Lymphoma: A SEER- Based Study

Population based registry study on large B-cell lymphoma mortality and morbidity in Finland

BACKGROUND

Large B-cell lymphomas (LBCLs) form a notable subgroup of lymphomas; however, their associated long-term comorbidities and mortality rates remain under-researched in real-world settings.

MATERIAL AND METHODS

This nationwide Finnish population-based matched cohort study included virtually all LBCL patients (N = 7,019) diagnosed from 2008 to 2019, alongside age, sex, and region-matched controls (1:1 ratio) without lymphoma. Diagnoses of LBCLs were obtained from the Finnish Cancer Registry, with data linked to additional nationwide registries. Baseline characteristics were summarised using descriptive statistics. Overall survival (OS) was estimated using the Kaplan-Meier method, while Cox regression was used to analyse factors associated with OS and evaluate the risk and associated factors of comorbidities considering the competing risk of death.

RESULTS

The 5-year survival rate for LBCL patients, median age 70.7 years and 52.7% male, was 50.0% (95% Confidence Interval [CI] 48.7% - 51.3%), compared to 82.6% (95% CI 81.5% - 83.6%) for controls. Among LBCL patients, older age and a higher Charlson comorbidity index were associated with increased mortality. Conversely, female sex, later diagnosis year, and radiation therapy were associated with improved survival. Patients with LBCL exhibited an elevated risk of long-term comorbidities, including solid tumours, hematological and skin cancers, lung and thyroid diseases, mental and behavioral disorders, and cardiovascular diseases. After 12 years of follow-up, lymphoma accounted for the primary cause of death in approximately 43% of LBCL patients.

INTERPRETATION

Large B-cell lymphomas are linked with significant long-term comorbidities and elevated mortality rates.

Development and validation of a novel risk stratification model and a survival rate calculator for diffuse large B-cell lymphoma in the rituximab era: a multi-institutional cohort study

BACKGROUND

This study aimed to develop and validate a novel risk stratification model and a web-based survival rate calculator to improve discriminative and predictive accuracy for diffuse large B-cell lymphoma (DLBCL) in the rituximab era.

METHODS

We retrospectively collected pre-treatment data from 873 primary DLBCL patients who received R-CHOP-based immunochemotherapy regimens at the Cancer Hospital, Chinese Academy of Medical Sciences, from January 1, 2005, to December 31, 2018. An independent cohort of 175 DLBCL patients from Fujian Cancer Hospital was used for external validation.

FINDINGS

Age, ECOG PS, number of extranodal sites, Ann Arbor stage, bulky disease, and LDH levels were screened to develop the nomogram and web-based survival rate calculator. The C-index of the nomogram in the training, internal validation, and external validation cohorts was 0.761, 0.758, and 0.768, respectively. The risk stratification model generated based on the nomogram effectively stratified patients into three distinct risk groups. K-M survival curves demonstrated that the novel risk stratification model exhibited a superior level of predictive accuracy compared to IPI, R-IPI, and NCCN-IPI both in training and two validation cohorts. Additionally, the area under the curve (AUC) value of the novel model (0.763) for predicting 5-year overall survival rates was higher than those of IPI (0.749), R-IPI (0.725), and NCCN-IPI (0.727) in the training cohort. Similar results were observed in both internal and external validation cohort.

CONCLUSIONS

In conclusion, we have successfully developed and validated a novel risk stratification model and a web-based survival rate calculator that demonstrated superior discriminative and predictive accuracy compared to IPI, R-IPI, and NCCN-IPI in the rituximab era.

Deep learning model for predicting the survival of patients with primary gastrointestinal lymphoma based on the SEER database and a multicentre external validation cohort

PURPOSE

Due to the rarity of primary gastrointestinal lymphoma (PGIL), the prognostic factors and optimal management of PGIL have not been clearly defined. We aimed to establish prognostic models using a deep learning algorithm for survival prediction.

METHODS

We collected 11,168 PGIL patients from the Surveillance, Epidemiology, and End Results (SEER) database to form the training and test cohorts. At the same time, we collected 82 PGIL patients from three medical centres to form the external validation cohort. We constructed a Cox proportional hazards (CoxPH) model, random survival forest (RSF) model, and neural multitask logistic regression (DeepSurv) model to predict PGIL patients' overall survival (OS).

RESULTS

The 1-, 3-, 5-, and 10-year OS rates of PGIL patients in the SEER database were 77.1%, 69.4%, 63.7%, and 50.3%, respectively. The RSF model based on all variables showed that the top three most important variables for predicting OS were age, histological type, and chemotherapy. The independent risk factors for PGIL patient prognosis included sex, age, race, primary site, Ann Arbor stage, histological type, symptom, radiotherapy, and chemotherapy, according to the Lasso regression analysis. Using these factors, we built the CoxPH and DeepSurv models. The DeepSurv model's C-index values were 0.760 in the training cohort, 0.742 in the test cohort, and 0.707 in the external validation cohort, which demonstrated that the DeepSurv model performed better compared to the RSF model (0.728) and the CoxPH model (0.724). The DeepSurv model accurately predicted 1-, 3-, 5- and 10-year OS. Both calibration curves and decision curve analysis curves demonstrated the superior performance of the DeepSurv model. We developed the DeepSurv model as an online web calculator for survival prediction, which can be accessed at http://124.222.228.112:8501/ .

CONCLUSIONS

This DeepSurv model with external validation is superior to previous studies in predicting short-term and long-term survival and can help us make better-individualized decisions for PGIL patients.

A Novel Prognostic Model for Patients with Primary Gastric Diffuse Large B-Cell Lymphoma

Objectives. Primary gastric diffuse large B-cell lymphoma (PG-DLBCL) is a common phenotype of extranodal non-Hodgkin’s lymphoma (NHL). This research aims to identify a model for predicting overall survival (OS) and cancer-specific survival (CSS) in PG-DLBCL. Methods. A total of 1716 patients diagnosed with PG-DLBCL between 1975 and 2017 were obtained from the SEER database and further randomly divided into the training and validating cohorts at a ratio of 7 : 3. Univariate and multivariate cox analyses were conducted to determine significant variables for the construction of nomogram. The performance of the model was then assessed by the concordance index (C-index), the calibration plot, and the area under the receiver operating characteristic (ROC) curve (AUC). Results. Multivariate analysis revealed that age, race, insurance status, Ann Arbor stage, marital status, chemotherapy, and radiation therapy all showed a significant association with OS and CSS. These characteristics were applied to build a nomogram. In the training cohort, the discrimination of nomogram for OS and CSS prediction was excellent (C-index = 0.764, 95% CI, 0.744–0.784 and C-index = 0.756, 95% CI, 0.732–0.780). The AUC of the nomogram for predicting 3- and 5-year OS was 0.779 and 0.784 and CSS was 0.765 and 0.772. Similar results were also observed in the internal validation set. Conclusions. We have successfully established a novel nomogram for predicting OS and CSS in PG-DLBCL patients with good accuracy, which can help physicians to quickly and accurately complete the evaluation of survival probability, risk stratification, and therapeutic strategy at diagnosis.

A new prediction model for overall survival of elderly patients with solitary bone plasmacytoma: A population-based study

Background

Comprehensive studies on the prognosis of solitary bone plasmacytoma (SPB) are lacking, especially in elderly patients with SPB. This study aims to establish a novel nomogram and risk stratification system to predict the overall survival (OS) of elderly patients with SPB.

Methods

The data of elderly patients with SPB from 2000 to 2017 were identified in the SEER database. SPB patients were randomly assigned to the training set (n = 825) and validation set (n = 354). The Cox regression analysis was used to determine the independent risk factors for OS in elderly SPB patients. The nomogram was established and assessed by the area under the receiver operating curve (AUC), the consistency index (C-index), and the calibration plot. Patients were divided into low-, medium-, and high-risk groups based on the score of the nomogram. The Kaplan-Meier (K-M) curve was used to verify the differences in overall survival among the three groups.

Result

A total of 1,179 elderly patients with SPB were included in the study. Age at diagnosis, prior cancer before SPB, marital status, radiotherapy, and chemotherapy were independent risk factors of OS. The AUC of the 3, 5, and 8-year OS in the training and validation sets were between 0.707 and 0.860. The C-index and calibration plot also indicated that the nomogram has great predictive accuracy and robustness. After risk stratification, patients in the high-risk group had the worst OS.

Conclusion

A novel nomogram was built to predict the OS of elderly patients with SPB. It will help clinicians formulate more reasonable and personalized treatment strategies.

Development and External Validation of a Nomogram to Predict Cancer-Specific Survival in Patients with Primary Intestinal Non-Hodgkin Lymphomas

Purpose

Primary intestinal non-Hodgkin lymphoma (PINHL) is a biologically and clinically heterogeneous disease. Few individual prediction models are available to establish prognoses for PINHL patients. Herein, a novel nomogram was developed and verified to predict long-term cancer-specific survival (CSS) rates in PINHL patients, and a convenient online risk calculator was created using the nomogram.

Materials and Methods

Data on PINHL patients from January 1, 2004, to December 31, 2015, obtained from the Surveillance, Epidemiology, and End Results (SEER) database (n = 2372; training cohort), were analyzed by Cox regression to identify independent prognostic parameters for CSS. The nomogram was internally and externally validated in a SEER cohort (n = 1014) and a First Affiliated Hospital of Guangzhou University of Chinese Medicine (FAHGUCM) cohort (n = 37), respectively. Area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA) were used to evaluate nomogram performance.

Results

Five independent predictors were identified, namely, age, marital status, Ann Arbor Stage, B symptoms, and histologic type. The nomogram showed good performance in discrimination and calibration, with C-indices of 0.772 (95% CI: 0.754–0.790), 0.763 (95% CI: 0.734–0.792), and 0.851 (95% CI: 0.755–0.947) in the training, internal validation, and external validation cohorts, respectively. The calibration curve indicated that the nomogram was accurate, and DCA showed that the nomogram had a high clinical application value. AUC values indicated that the prediction accuracy of the nomogram was higher than that of Ann Arbor Stage (training cohort: 0.804 vs 0.630; internal validation cohort: 0.800 vs 0.637; external validation cohort: 0.811 vs 0.598), and Kaplan–Meier curves indicated the same.

Conclusion

A nomogram was developed to assist clinicians in predicting the survival of PINHL patients and in making optimal treatment decisions. An online calculator based on the nomogram was made available at https://cuifenzhang.shinyapps.io/DynNomapp/.

Surgery and Chemotherapy versus Chemotherapy Only in Older Persons with Primary Intestinal Diffuse Large B-Cell Lymphoma

Background

The management of primary intestinal diffuse large B cell lymphoma (PI-DLBCL) in elderly patients (aged >60 years) remains controversial. We conducted a retrospective study to assess the efficacy of different treatment strategies and prognostic factors for elderly Chinese patients with PI-DLBCL.

Patients and Methods

Forty-six untreated elderly patients with PI-DLBCL were included in this retrospective study. Twenty-four patients were treated with surgery (prior to chemotherapy) plus chemotherapy (SCT). The other 22 patients did not undergo surgery before chemotherapy (CT).

Results

Patients treated with SCT had a higher overall response rate of 91.7% than patients receiving CT, but the difference between groups was not significant (P=0.581). Regarding survival, SCT resulted in a greater 3-year overall survival (OS) rate (87.3% vs 56.9%, P=0.130) and significantly higher 3-year event-free survival (EFS) rate (74.1% vs 27.3%, P=0.002) than CT. The univariate analysis showed that male sex, advanced Lugano stage, poor performance status and chemotherapy alone were associated with a shorter EFS. Only the male sex was correlated with a shorter OS. The multivariate analysis showed that sex (P=0.040) and treatment strategy (P=0.022) were independent prognostic factors for EFS.

Conclusion

Surgery plus chemotherapy produced a better outcome for EFS, but not OS, than chemotherapy alone in elderly Chinese patients with PI-DLBCL.

Role of radiation therapy in primary tonsil large B cell lymphoma: a SEER-based analysis

Backgroud

Primary tonsil diffuse large B cell lymphoma (PT-DLBCL) is an uncommon disease entity. The role of radiation therapy (RT) in PT-DLBCL is debatable in both the pre- and post- rituximab era. The purpose of this study was to evaluate the treatment outcome and establish a prognostic model in PT-DLBCL based on the Surveillance, Epidemiology, and End Results (SEER) database.

Materials and methods

Data of 1214 PT-DLBCL patients diagnosed between 1975 and 2016 were extracted from SEER 18. The effect of RT was assessed for the entire cohort and subgroups by stages using univariate, multivariate Cox regression analyses and propensity score matching (PSM).

Results

The entire cohort included 1043 patients with early-stage (ES) PT-DLBCL and 171 patients with advanced-stage (AS) disease. A decreasing trend of RT utilization in the ES cohort after 2002 was observed. 47.4% of patients in ES received RT, whereas 25.1% in AS underwent RT. RT significantly improved overall survival in both univariate (P < 0.001) and multivariate (P = 0.002) analyses. PSM analysis further validated the survival advantage of RT (P = 0.002). A nomogram was established to predict the potential survival benefit. Subgroup analysis revealed RT was significantly associated with overall survival in ES patients of PT-DLBCL (P = 0.001) and in the rituximab era (P = 0.001) but not in those with AS disease (P = 0.241).

Conclusions

This population-based study encloses the largest sample of PT-DLBCL to date and demonstrates a favorable survival role of RT in early stages rather than advanced stages. The established nomogram helps to identify high risk patients to improve prognosis.

Update on B-cell lymphoproliferative disorders of the gastrointestinal tract

The gastrointestinal (GI) tract is home to a significant portion of the immune system, which interacts daily with the antigenic milieu of its contents. Therefore, the presence of white blood cells within the walls of the GI tract upon histologic examination is a familiar sight on GI biopsies-both in health and disease. The GI tract is the most common site of extranodal lymphomas, most of which are B-cell neoplasms. Here, we review common and uncommon B-cell neoplasms of the GI tract - extranodal marginal zone lymphoma of mucosa-associated lymphoid tissue (MALT lymphoma), mantle cell lymphoma, duodenal-type follicular lymphoma, diffuse large B-cell lymphoma, plasmablastic lymphoma, EBV-positive mucocutaneous ulcer, and post-transplant lymphoproliferative disorders - with special focus on literature published during the past five years. Along with the other articles in this edition of Seminars in Diagnostic Pathology, it is the authors' hope that this review proves to be a useful resource in the workup of the array of hematopoietic processes that can involve the GI tract.

A nomogram model to predict the venous thromboembolism risk after surgery in patients with gynecological tumors

OBJECTIVE

Venous thromboembolism (VTE) is a common post-surgical complication of gynecological malignant tumors that has serious implications on the prognosis and quality-of-life of patients. However, there exists only a few recognized specific evaluation models for the occurrence of VTE after gynecological malignant tumor surgery. We aimed to establish a nomogram model that could predict the probability of post-surgical VTE in patients with gynecological malignancies.

METHODS

We collected the clinical information of 673 patients who underwent surgery for gynecological malignant tumor in our hospital between January 2014 and May 2020. To reduce bias from confounding factors between groups, a 1:1 ratio propensity score matching (PSM) method was performed; meanwhile, univariate and multivariate analyses were applied to analyze the risk factors of VTE after surgeries. A nomogram prediction model was accordingly established and internally validated.

RESULTS

The predictors contained in the nomogram model included age, D-dimer value, body mass index (BMI), and surgical approach. The C-index of the model was 0.721 (95% confidence interval: 0.644-0.797), with good discrimination and calibration effect. The internally verified C-index value was 0.916. Decision curve analysis confirmed that the nomogram model was clinically useful when the incidence of thrombosis in patients was 10-75%.

CONCLUSIONS

Considering the risk factors of VTE after surgery for gynecological malignant tumor, a high-performance nomogram model was established and then validated to provide individual risk assessment and guide treatment decisions.