Tumour-free distance: a novel prognostic marker in patients with early-stage cervical cancer treated by primary surgery
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
33318656
PubMed Central
PMC7961006
DOI
10.1038/s41416-020-01204-w
PII: 10.1038/s41416-020-01204-w
Knihovny.cz E-zdroje
- MeSH
- adenokarcinom patologie chirurgie MeSH
- dospělí MeSH
- hysterektomie MeSH
- lidé středního věku MeSH
- lidé MeSH
- lokální recidiva nádoru patologie chirurgie MeSH
- lymfatické uzliny patologie chirurgie MeSH
- míra přežití MeSH
- nádory děložního čípku patologie chirurgie MeSH
- následné studie MeSH
- prognóza MeSH
- retrospektivní studie MeSH
- senioři MeSH
- spinocelulární karcinom patologie chirurgie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Models predicting recurrence risk (RR) of cervical cancer are used to tailor adjuvant treatment after radical surgery. The goal of our study was to compare available prognostic factors and to develop a prognostic model that would be easy to standardise and use in routine clinical practice. METHODS: All consecutive patients with early-stage cervical cancer treated by primary surgery in a single referral centre (01/2007-12/2016) were eligible if assessed by standardised protocols for pre-operative imaging and pathology. Fifteen prognostic markers were evaluated in 379 patients, out of which 320 lymph node (LN)-negative. RESULTS: The best predictive model for the whole cohort entailed a combination of tumour-free distance (TFD) ≤ 3.5 mm and LN positivity, which separated two subgroups with a substantially distinct RR 36% and 6.5%, respectively. In LN-negative patients, a combination of TFD ≤ 3.5 mm and adenosquamous tumour type separated a group of nine patients with RR 33% from the rest of the group with 6% RR. CONCLUSIONS: A newly identified prognostic marker, TFD, surpassed all traditional tumour-related markers in the RR assessment. Predictive models combining TFD, which can be easily accessed on pre-operative imaging, with LN status or tumour type can be used in daily practice and can help to identify patients with the highest RR.
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