Objective: This is the second of a two-part paper exploring the use of a more quantitative approach to both cytology and histology disease severity measurements. In Part I the problem of artificial cut-off points was discussed and a semi-quantitative solution to the problem proposed. In Part II quantitative methods are proposed that are used to predict the estimated progression probability (EPP) to invasive cancer.
Methods: Based on models derived from published data the grade number (GN) is related to the EPP to invasive cancer over the next 10 years for both cytology (CEPP) and histology (HEPP) using a look-up table. CEPP and HEPP are then adjusted by other factors such as age, persistence, HPV result, number of cells and lesion size to obtain the adjusted CEPP and HEPP (ACEPP and (AHEPP). The two factors can be combined to produce an adjusted weighted estimated progression potential using the formula AWEPP √((ACEPP + AHEPP)/2) × AHEPP) using a two to one bias in favour of the histology.
Results: As an example of the methodology consider a slide estimated as showing a 60% probability of moderate dyskaryosis (HSIL favouring CIN2) and 40% probability of mild dyskaryosis (LSIL favouring CIN1). The GN number would be 1.6 (as described in Part I) and the EPP over the next 10 years 0.78%. For a woman aged 52 years (correction factor ×2.0) with a second mildly dyskaryotic smear (correction factor ×1.25) and >50 dyskaryotic cells (correction factor 1.5) the ACEPP would be 0.78 × 2.00 × 1.25 × 1.5 = 2.9%. If the HEPP on histology was 50:50 between CIN1 and CIN2, the AHEPP can be calculated as 1.4%. The AWEPP would be √((2.9 + 1.4)/2 × 1.4) = 1.7%. The final estimate of disease progression potential based on both cytology and histology is 1.7% over 10 years.
Conclusions: These quantitative approaches based on adjusted and weighted EPP provide a framework suitable for research, audit and comparison between screening centres, and for tailoring criteria for colposcopy referral and treatment. Further research is required to improve the estimates given in the paper.
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http://dx.doi.org/10.1111/j.1365-2303.2010.00815.x | DOI Listing |
Clin Infect Dis
January 2025
GSK, Wavre, Belgium.
Background: In this phase 3 trial of an investigational maternal respiratory syncytial virus prefusion F protein-based vaccine (RSVPreF3-Mat), a higher rate of preterm birth was observed in the vaccine (6.8%) versus the placebo group (4.9%).
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January 2025
Maine et Loire, Univ Angers, CHU Angers, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail) - UMR_S 1085, IRSET-ESTER, SFR ICAT, CAPTV CDC, 49000 Angers, France.
Background: Systemic sclerosis (SSc) is the connective tissue disease with the highest individual mortality. Crystalline silica is known to be an occupational risk factor for SSc. To assess past crystalline silica exposure, we aimed to study the validity of a job exposure matrix (JEM) to assess occupational exposure to crystalline silica compared to specific occupational interviews in two populations of SSc patients.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Department of Dermatology, Hospital Universitario Ramon y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain, Madrid, Spain.
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January 2025
AP-HP, Sorbonne Université, Liver Intensive Care Unit, Hepatogastroenterology Department, La Pitié-Salpêtrière Hospital, 47-83 Boulevard de l'Hôpital, Paris 75013, France.
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Approach And Results: We conducted a retrolective analysis from a prospective cohort of patients hospitalized for AD.
Neurol Neuroimmunol Neuroinflamm
March 2025
Department of Neurology and Experimental Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt- Universität zu Berlin.
Background And Objectives: Cognitive deficits represent a major long-term complication of anti-leucine-rich, glioma-inactivated 1 encephalitis (LGI1-E). Although severely affecting patient outcomes, the structural brain changes underlying these deficits remain poorly understood. In this study, we hypothesized a link between white matter (WM) networks and cognitive outcomes in LGI1-E.
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