Baseline predictors of negative and incomplete pleural cytology in patients with suspected pleural malignancy - Data supporting 'Direct to LAT' in selected groups.


Journal

Lung cancer (Amsterdam, Netherlands)
ISSN: 1872-8332
Titre abrégé: Lung Cancer
Pays: Ireland
ID NLM: 8800805

Informations de publication

Date de publication:
07 2019
Historique:
received: 15 01 2019
revised: 09 04 2019
accepted: 15 05 2019
entrez: 16 6 2019
pubmed: 16 6 2019
medline: 7 3 2020
Statut: ppublish

Résumé

Negative effusion cytology is more common in certain forms of Malignant Pleural Effusion (MPE) and results in pathway delay. Local Anaesthetic Thoracoscopy (LAT) is extremely sensitive and safe but cannot be offered to all. A stratified pathway, including 'Direct to LAT' in selected cases could enhance patient experience but requires reliable baseline predictors of unhelpful cytology, including both negative (no malignant cells) and incomplete results (malignant cells identified but predictive markers failed), since pleural biopsies will be required in the latter for optimal management. This retrospective analysis of a prospective multi-centre study, sought to identify baseline features for pathway rationalization. 363/638 (57%) of patients recruited to the DIAPHRAGM study (ISRCTN10079972) were included. Prospective data, including final diagnoses, asbestos exposure and fluid cytology results were supplemented by retrospective Computed Tomography (CT) and predictive marker reports. Independent predictors of negative and incomplete cytology were determined by multivariable logistic regression. Contingency tables were used to assess diagnostic value of cytology in associated phenotypes. 238/363 (66%) patients were diagnosed with MPE (18 tumour types). Fluid cytology was negative in 151/238 (63%) and independently associated with asbestos-exposure (Odds Ratio (OR) 5.34) and a malignant CT (OR 2.25). When both features were recorded the sensitivity and negative predictive value of fluid cytology were 19% (95% CI 11-30%) and 9% (95% CI 4-20%)), respectively. Cytology was incomplete in 34/238 (14%), i.e. 47% of positive cytology cases) but was not associated with any baseline feature. ORs for incomplete cytology in Ovarian, Breast, Renal and Lung Cancer were 83, 22, 21 and 9, respectively. Negative cytology is extremely likely in patients with asbestos exposure and a malignant CT report. A 'Direct-to-LAT' approach may be appropriate in this setting. No baseline predictors of incomplete cytology were identified.

Identifiants

pubmed: 31200818
pii: S0169-5002(19)30462-3
doi: 10.1016/j.lungcan.2019.05.017
pii:
doi:

Substances chimiques

Biomarkers, Tumor 0
Asbestos 1332-21-4

Types de publication

Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

123-129

Subventions

Organisme : Chief Scientist Office
ID : ETM/285
Pays : United Kingdom

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Selina Tsim (S)

Glasgow Pleural Disease Unit, Queen Elizabeth University Hospital, Glasgow, UK.

Sarah Paterson (S)

Respiratory Medicine, Manchester University NHS Foundation Trust, Wythenshawe Hospital, North West Lung Centre, Manchester, UK.

Douglas Cartwright (D)

Glasgow Pleural Disease Unit, Queen Elizabeth University Hospital, Glasgow, UK.

Christopher J Fong (CJ)

Glasgow Pleural Disease Unit, Queen Elizabeth University Hospital, Glasgow, UK.

Laura Alexander (L)

Cancer Research UK Clinical Trials Unit, University of Glasgow, Glasgow, UK.

Caroline Kelly (C)

Cancer Research UK Clinical Trials Unit, University of Glasgow, Glasgow, UK.

Jayne Holme (J)

Respiratory Medicine, Manchester University NHS Foundation Trust, Wythenshawe Hospital, North West Lung Centre, Manchester, UK.

Matthew Evison (M)

Respiratory Medicine, Manchester University NHS Foundation Trust, Wythenshawe Hospital, North West Lung Centre, Manchester, UK.

Kevin G Blyth (KG)

Glasgow Pleural Disease Unit, Queen Elizabeth University Hospital, Glasgow, UK; Institute of Infection, Immunity & Inflammation, University of Glasgow, Glasgow, UK. Electronic address: kevin.blyth@ggc.scot.nhs.uk.

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Classifications MeSH