ReviewPathology2018
Pattern based classification of endocervical adenocarcinoma: a review.
Review in Pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 17 citations in OpenAlex.
- Molecular correlates of invasion pattern in HPV-associated endocervical adenocarcinoma: emergence of two distinct risk-stratified tiers.Histopathology · 2023Article
- Grading of Endocervical Adenocarcinomas: Review of the Literature and Recommendations From the International Society of Gynecological Pathologists.International journal of gynecological pathology : official journal of the International Society of Gynecological Pathologists · 2021Review
- International Endocervical Adenocarcinoma Criteria and Classification: Validation and Interobserver Reproducibility.The American journal of surgical pathology · 2019Article
- The pattern is the issue: recent advances in adenocarcinoma of the uterine cervix.Virchows Archiv : an international journal of pathology · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
While endocervical adenocarcinoma is comprised of several histological subtypes, the most common subtype is human papillomavirus-associated usual type, and management of these tumours is primarily determined by FIGO (International Federation of Gynecology and Obstetrics) stage, a clinically based staging system. Early stage cervical cancer is determined by the pathological evaluation of tumour microscopic measurement (depth of invasion), which can be particularly challenging because of the lack of a defined point of origin. Yet important treatment decisions, cone versus radical surgery, are based on this imperfect system, resulting in overtreatment and related morbidities in many patients for whom it may not be necessary. There is a growing consensus, however, for a more conservative approach, one that reduces morbidity and prevents loss of fertility in these (often young) patients. This movement has been supported, in part, by the development of a morphology based risk stratification system which was devised in order to recognise those tumours that, while invasive, could potentially be treated more conservatively. In this review, we provide the reader with the background and rationale for a more conservative approach in treating endocervical adenocarcinoma, summarise the risk stratification system, and review the system's utility and reproducibility. In addition, we comment on recent updates that attempt to further refine the system. The application of this morphology based classification could help identify a subset of patients with endocervical adenocarcinoma (who would otherwise undergo radical surgery based on FIGO staging alone) that have good clinical outcomes and could be treated more conservatively.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.