Prognostic factors in patients with gastric adenocarcinoma using competing-risk analysis: a study of cases in the SEER database

Primary gastric non-Hodgkin lymphomas: Recent advances regarding disease pathogenesis and treatment

Primary gastric lymphomas (PGLs) are distinct lymphoproliferative neoplasms described as heterogeneous entities clinically and molecularly. Their main histological types are diffuse large B-cell lymphoma (DLBCL) or mucosa-associated lymphoma tissue. PGL has been one of the main fields of clinical research of our group in recent years. Although gastric DLBCLs are frequent, sufficient data to guide optimal care are scarce. Until today, a multidisciplinary approach has been applied, including chemotherapy, surgery, radiotherapy or a combination of these treatments. In this minireview article, we provide an overview of the clinical manifestations, diagnosis and staging of these diseases, along with their molecular pathogenesis and the most important related clinical published series. We then discuss the scientific gaps, perils and pitfalls that exist regarding the aforementioned studies, in parallel with the unmet need for future research and comment on the proper methodology for such retrospective studies. Aiming to fill this gap, we retrospectively evaluated the trends in clinical presentation, management and outcome among 165 patients with DLBCL PGL who were seen in our institutions in 1980-2014. The study cohort was divided into two subgroups, comparing the main 2 therapeutic options [cyclophosphamide doxorubicin vincristine prednisone (CHOP) vs rituximab-CHOP (R-CHOP)]. A better outcome with immunochemotherapy (R-CHOP) was observed. In the next 2 mo, we will present the update of our study with the same basic conclusion.

Identifying Factors Affecting Cancer-related Death in Patients with Adenocarcinoma Gastric Cancer; An Analysis in the Presence of Competing Risks

Background: Adenocarcinoma is the most common type of gastric cancer that has shorter survival than other types of gastric cancer. The death of patients with this type of cancer may be due to the progression of cancer or other related causes. Objectives: The aim of this study is to determine the factors affecting death due to the cancer progression in gastric cancer patients with the diagnosis of adenocarcinoma, using competing risk models. Methods: This retrospective cohort study was performed on 306 gastric cancer patients diagnosed with adenocarcinoma referring to Imam Khomeini clinic in Hamadan from 2002 to 2017. Death due to the cancer progression was considered an interest event and death due to without progression as a competing event. To determine the effect of covariates on hazard, the cause-specific and subdistribution hazard regression models were used. Data analysis was performed, using R3.6.1 software and cmprsk and survival packages. Results: The mean (SD) age of patients was 62.3 (12.5) years and 74.3% were male. The effect of the stage, the number of involved lymphomas, and the type of treatment were significant on the hazard of death due to the disease progression in both cause-specific and subdistribution hazard models. Conclusions: The results showed that most deaths occur in the first 3 years of follow-up. The higher stage and higher number of lymph nodes have increased the hazard of death but supplementary treatment significantly decreased the hazard of death due to cancer progression in adenocarcinoma gastric cancer patients in both competing risk models.

Competing-risks nomograms for predicting cause-specific mortality in parotid-gland carcinoma: A population-based analysis

INTRODUCTION

Parotid-gland carcinoma (PGC) is a relatively rare tumor that comprises a group of heterogeneous histologic subtypes. We used the Surveillance, Epidemiology, and End Results (SEER) program database to apply a competing-risks analysis to PGC patients, and then established and validated predictive nomograms for PGC.

METHODS

Specific screening criteria were applied to identify PGC patients and extract their clinical and other characteristics from the SEER database. We used the cumulative incidence function to estimate the cumulative incidence rates of PGC-specific death (GCD) and other cause-specific death (OCD), and tested for differences between groups using Gray's test. We then identified independent prognostic factors by applying the Fine-Gray proportional subdistribution hazard approach, and constructed predictive nomograms based on the results. Calibration curves and the concordance index (C-index) were employed to validate the nomograms.

RESULTS

We finally identified 4,075 eligible PGC patients who had been added to the SEER database from 2004 to 2015. Their 1-, 3-, and 5-year cumulative incidence rates of GCD were 10.1%, 21.6%, and 25.7%, respectively, while those of OCD were 2.9%, 6.6%, and 9.0%. Age, race, World Health Organization histologic risk classification, differentiation grade, American Joint Committee on Cancer (AJCC) T stage, AJCC N stage, AJCC M stage, and RS (radiotherapy and surgery status) were independent predictors of GCD, while those of OCD were age, sex, marital status, AJCC T stage, AJCC M stage, and RS. These factors were integrated for constructing predictive nomograms. The results for calibration curves and the C-index suggested that the nomograms were well calibrated and had good discrimination ability.

CONCLUSION

We have used the SEER database to establish-to the best of our knowledge-the first competing-risks nomograms for predicting the 1-, 3-, and 5-year cause-specific mortality in PGC. The nomograms showed relatively good performance and can be used in clinical practice to assist clinicians in individualized treatment decision-making.

Competing-Risk Nomograms for Predicting the Prognosis of Patients With Infiltrating Lobular Carcinoma of the Breast

BACKGROUND

Infiltrating lobular carcinoma (ILC) is the second most common histologic subtype of breast cancer. We assessed the rates of cause-specific death in ILC patients with the aim of establishing competing-risk nomograms for predicting their prognosis.

PATIENTS AND METHODS

Data on ILC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The cumulative incidence function was used to calculate the cumulative incidence rates of cause-specific death, and Gray's test was applied to test the differences in cumulative incidence rates among groups. We then identified independent prognostic factors by applying the Fine-Gray proportional subdistribution hazard analysis method and established nomograms based on the results. Calibration curves and the concordance index were employed to validate the nomograms.

RESULTS

The study enrolled 11,361 patients. The 3-, 5-, and 10-year overall cumulative incidence rates for those who died of ILC were 3.1%, 6.2%, and 12.2%, respectively, whereas the rates for those who died from other causes were 3.2%, 5.8%, and 14.1%. Age, marriage, grade, size, regional node positivity, American Joint Committee on Cancer M stage, progesterone receptor, and surgery were independent prognostic factors for dying of ILC, whereas the independent prognostic factors for dying of other causes were age, race, marriage, size, radiation, and chemotherapy. The nomograms were well calibrated and had good discrimination ability.

CONCLUSION

We applied competing-risk analysis to ILC patients based on the SEER database and established nomograms that perform well in predicting the cause-specific death rates at 3, 5, and 10 years after the diagnosis.

Prognostic factors in patients with gallbladder adenocarcinoma identified using competing-risks analysis: A study of cases in the SEER database

A competing-risks model was developed in this study to identify the significant prognostic factors and evaluate the cumulative incidence of cause-specific death in gallbladder adenocarcinoma (GBAC), with the aim of providing guidance on effective clinical treatments.All patients with GBAC in the Surveillance, Epidemiology, and End Results (SEER) database during 1973 to 2015 were identified. The potential prognostic factors were identified using competing-risks analyses implemented using the R and SAS statistical software packages. We calculated the cumulative incidence function (CIF) for cause-specific death and death from other causes at each time point. The Fine-Gray proportional-subdistribution-hazards model was then applied in univariate and multivariate analyses to test the differences in CIF between different groups and identify independent prognostic factors.This study included 3836 eligible patients who had been enrolled from 2004 to 2015 in the SEER database. The univariate analysis indicated that age, race, AJCC stage, RS, tumor size, SEER historic stage, grade, surgery, radiotherapy, chemotherapy and adjuvant therapy (RCT, SRT, SCT and SRCT) were significant factors affecting the probability of death due to GBAC. The multivariate analysis indicated that age, race, AJCC stage, RS status, tumor size, grade and SRT were independent prognostic factors affecting GBAC cancer-specific death. A nomogram model was constructed based on multivariate models for death related to GBAC.We have constructed the first competing-risks nomogram for GBAC. The model was found to perform well. This novel validated prognostic model may facilitate the choosing of beneficial treatment strategies and help when predicting survival.