Response to R-CHOP in HPV-related squamous cell carcinoma of base of tongue: a case report

Synchronous or collision solid neoplasms and lymphomas: A systematic review of 308 case reports

BACKGROUND

The presence of a lymphoma associated with a solid synchronous neoplasm or collision neoplasm has been rarely in the literature, and a detailed characterization of these cases is lacking to date.

OBJECTIVE

To describe the main clinicopathological features of synchronous/collision tumors.

METHODS

A systematic search in PubMed, Scielo, and Virtual Health Library literature databases for cases or case series of synchronous or collision lymphoma and other solid neoplasms reported up to March 2021 was performed. Three reviewers independently screened the literature, extracted data, and assessed the quality of the included studies. The systematic review was performed following the Preferred Reporting Items for Systematic Meta-Analyses guidelines.

RESULTS

Mean age of patients was 62.9 years (52.9% men). A total of 308 cases were included (62% synchronous and 38% collision). The most frequent location of both synchronous and collision tumors was the gastrointestinal tract with the most common solid neoplasm being adenocarcinoma, and the most frequent lymphoma diffuse large B-cell lymphoma (21.7%) and mucosa-associated lymphoid tissue lymphoma (20.4%). Of the total number of mucosa-associated lymphoid tissue lymphomas and gastric adenocarcinomas, the presence of Helicobacter pylori infection was documented in 47.3% of them. Only 2% of all cases had a previous history of lymphoma. Thus, in most cases (98%), lymphoma was discovery incidentally. In addition, nodal lymphoma was associated with metastasis in 29 (9.4%) cases as collision tumor, most commonly (90%) in locoregional lymph nodes of the solid neoplasm.

CONCLUSIONS

The frequent association of some type of B-cell lymphoma and adenocarcinoma in synchronous/collision tumors of the gastrointestinal tract points to common pathogenic mechanisms in both neoplasia, particularly related to chronic inflammation in this location. In most cases, lymphoma identified in locoregional lymph nodes or distant of a carcinoma seems to represent an incidental finding during the carcinoma diagnostic/therapeutic approach. A synergy between carcinoma and lymphoma (involving inflammation and immunosuppression mechanisms) may favor tumor progression and dissemination. A better understating of the interactions lymphoma/carcinoma in the setting of synchronous/collision tumors may help to improve patient management and prognosis.

Evidence-Based Medicine in Otolaryngology, Part XI: Modeling and Analysis to Support Decisions

OBJECTIVE

To provide a resource to educate clinical decision makers about the analyses and models that can be employed to support data-driven choices.

DATA SOURCES

Published studies and literature regarding decision analysis, decision trees, and models used to support clinical decisions.

REVIEW METHODS

Decision models provide insights into the evidence and its implications for those who make choices about clinical care and resource allocation. Decision models are designed to further our understanding and allow exploration of the common problems that we face, with parameters derived from the best available evidence. Analysis of these models demonstrates critical insights and uncertainties surrounding key problems via a readily interpretable yet quantitative format. This 11th installment of the Evidence-Based Medicine in Otolaryngology series thus provides a step-by-step introduction to decision models, their typical framework, and favored approaches to inform data-driven practice for patient-level decisions, as well as comparative assessments of proposed health interventions for larger populations.

CONCLUSIONS

Information to support decisions may arise from tools such as decision trees, Markov models, microsimulation models, and dynamic transmission models. These data can help guide choices about competing or alternative approaches to health care.

IMPLICATIONS FOR PRACTICE

Methods have been developed to support decisions based on data. Understanding the related techniques may help promote an evidence-based approach to clinical management and policy.