ReviewCytoJournal2022
Role of immunocytochemistry in cervical cancer screening.
Review in CytoJournal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 8 citations in OpenAlex.
- Hyperspectral Imaging of Whole-Cell Region for Differentiating Cervical Squamous Intraepithelial Lesion Cytology.Cancer medicine · 2026Article
- Integrative molecular diagnostics for HPV-driven cervical carcinogenesis: a translational review of mechanisms and multimodal risk stratification.Frontiers in oncology · 2026Review
- Comprehensive Evaluation of the Utility of Cell Block Use in ThinPrep Liquid-Based Cervical Specimens.Turk patoloji dergisi · 2025Article
- Field-Applicable Loop-Mediated Isothermal Amplification for the Detection of Seven Common Human Papillomavirus Subtypes.Tropical medicine and infectious disease · 2024Article
- Clinical utility of HPV typing and quantification combined with PAX1/ZNF582 methylation detection in accurate cervical cancer screening.CytoJournal · 2023Article
- Spectrum of cervicovaginal Pap smears in newly established tertiary care medical institute.CytoJournal · 2023Article
- Deep Learning-Based Screening of Urothelial Carcinoma in Whole Slide Images of Liquid-Based Cytology Urine Specimens.Cancers · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The cervical cancer screening has been based conventionally on cytologic analysis. With advances in understanding the role of human papillomavirus, cotesting has been applied. But most of the patients subjected to colposcopy did not benefit, except in cases with HSIL [high-grade squamous intraepithelial lesion] cytology. Because of this, a step to increase the sensitivity to detect cancers and pre-cancers but with higher specificity with minimal overdiagnosis leading to prevention of unindicated cervical biopsies is highly desired. Such triaging step in cases with abnormal screening results is expected to minimize invasive interventions because of low false positivity. With availability of methodologies leading to quantitatively and qualitatively enhanced cell-blocks from residual liquid based cytology specimens, immunostaining can be performed for multiple immunomarkers with potential objectivity to triage initial screening test results. This is enhanced further with inclusion of AV marker in the cell-blocks and application of SCIP (subtractive coordinate immunoreactivity pattern) approach. The cell-blocks are also resource for performing other ancillary studies including molecular pathology and proteomics/metabolomics as potential tests in future. This review explores application of residual liquid based cytology specimen for cell-blocking with application of ancillary studies in algorithmic manner as adjunct to ASCCP management guidelines for improved patient care.
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.