University of Hertfordshire

From the same journal

By the same authors

Standard

Comparison of Longitudinal CA125 Algorithms as a First-Line Screen for Ovarian Cancer in the General Population. / Blyuss, Oleg; Burnell, Matthew; Ryan, Andy; Gentry-Maharaj, Aleksandra; Mariño, Inés P; Kalsi, Jatinderpal; Manchanda, Ranjit; Timms, John F; Parmar, Mahesh; Skates, Steven J; Jacobs, Ian; Zaikin, Alexey; Menon, Usha.

In: Clinical Cancer Research, Vol. 24, No. 19, 01.10.2018, p. 4726-4733.

Research output: Contribution to journalArticlepeer-review

Harvard

Blyuss, O, Burnell, M, Ryan, A, Gentry-Maharaj, A, Mariño, IP, Kalsi, J, Manchanda, R, Timms, JF, Parmar, M, Skates, SJ, Jacobs, I, Zaikin, A & Menon, U 2018, 'Comparison of Longitudinal CA125 Algorithms as a First-Line Screen for Ovarian Cancer in the General Population', Clinical Cancer Research, vol. 24, no. 19, pp. 4726-4733. https://doi.org/10.1158/1078-0432.CCR-18-0208

APA

Blyuss, O., Burnell, M., Ryan, A., Gentry-Maharaj, A., Mariño, I. P., Kalsi, J., Manchanda, R., Timms, J. F., Parmar, M., Skates, S. J., Jacobs, I., Zaikin, A., & Menon, U. (2018). Comparison of Longitudinal CA125 Algorithms as a First-Line Screen for Ovarian Cancer in the General Population. Clinical Cancer Research, 24(19), 4726-4733. https://doi.org/10.1158/1078-0432.CCR-18-0208

Vancouver

Author

Blyuss, Oleg ; Burnell, Matthew ; Ryan, Andy ; Gentry-Maharaj, Aleksandra ; Mariño, Inés P ; Kalsi, Jatinderpal ; Manchanda, Ranjit ; Timms, John F ; Parmar, Mahesh ; Skates, Steven J ; Jacobs, Ian ; Zaikin, Alexey ; Menon, Usha. / Comparison of Longitudinal CA125 Algorithms as a First-Line Screen for Ovarian Cancer in the General Population. In: Clinical Cancer Research. 2018 ; Vol. 24, No. 19. pp. 4726-4733.

Bibtex

@article{8b0e4a2365c245ec9339fa4bf40a9342,
title = "Comparison of Longitudinal CA125 Algorithms as a First-Line Screen for Ovarian Cancer in the General Population",
abstract = "Purpose: In the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), women in the multimodal (MMS) arm had a serum CA125 test (first-line), with those at increased risk, having repeat CA125/ultrasound (second-line test). CA125 was interpreted using the {"}Risk of Ovarian Cancer Algorithm{"} (ROCA). We report on performance of other serial algorithms and a single CA125 threshold as a first-line screen in the UKCTOCS dataset.Experimental Design: 50,083 post-menopausal women who attended 346,806 MMS screens were randomly split into training and validation sets, following stratification into cases (ovarian/tubal/peritoneal cancers) and controls. The two longitudinal algorithms, a new serial algorithm, method of mean trends (MMT) and the parametric empirical Bayes (PEB) were trained in the training set and tested in the blinded validation set and the performance characteristics, including that of a single CA125 threshold, were compared.Results: The area under receiver operator curve (AUC) was significantly higher (P = 0.01) for MMT (0.921) compared with CA125 single threshold (0.884). At a specificity of 89.5%, sensitivities for MMT [86.5%; 95% confidence interval (CI), 78.4-91.9] and PEB (88.5%; 95% CI, 80.6-93.4) were similar to that reported for ROCA (sensitivity 87.1%; specificity 87.6%; AUC 0.915) and significantly higher than the single CA125 threshold (73.1%; 95% CI, 63.6-80.8).Conclusions: These findings from the largest available serial CA125 dataset in the general population provide definitive evidence that longitudinal algorithms are significantly superior to simple cutoff values for ovarian cancer screening. Use of these newer algorithms requires incorporation into a multimodal strategy. The results highlight the importance of incorporating serial change in biomarker levels in cancer screening/early detection strategies. Clin Cancer Res; 24(19); 4726-33. {\textcopyright}2018 AACR.",
keywords = "Aged, Algorithms, Biomarkers, Tumor/blood, CA-125 Antigen/blood, Early Detection of Cancer, Female, Humans, Longitudinal Studies, Membrane Proteins/blood, Middle Aged, Ovarian Neoplasms/blood, Risk Factors, Ultrasonography, United Kingdom",
author = "Oleg Blyuss and Matthew Burnell and Andy Ryan and Aleksandra Gentry-Maharaj and Mari{\~n}o, {In{\'e}s P} and Jatinderpal Kalsi and Ranjit Manchanda and Timms, {John F} and Mahesh Parmar and Skates, {Steven J} and Ian Jacobs and Alexey Zaikin and Usha Menon",
note = "{\textcopyright}2018 American Association for Cancer Research.",
year = "2018",
month = oct,
day = "1",
doi = "10.1158/1078-0432.CCR-18-0208",
language = "English",
volume = "24",
pages = "4726--4733",
journal = "Clinical Cancer Research",
issn = "1078-0432",
publisher = "American Association for Cancer Research Inc.",
number = "19",

}

RIS

TY - JOUR

T1 - Comparison of Longitudinal CA125 Algorithms as a First-Line Screen for Ovarian Cancer in the General Population

AU - Blyuss, Oleg

AU - Burnell, Matthew

AU - Ryan, Andy

AU - Gentry-Maharaj, Aleksandra

AU - Mariño, Inés P

AU - Kalsi, Jatinderpal

AU - Manchanda, Ranjit

AU - Timms, John F

AU - Parmar, Mahesh

AU - Skates, Steven J

AU - Jacobs, Ian

AU - Zaikin, Alexey

AU - Menon, Usha

N1 - ©2018 American Association for Cancer Research.

PY - 2018/10/1

Y1 - 2018/10/1

N2 - Purpose: In the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), women in the multimodal (MMS) arm had a serum CA125 test (first-line), with those at increased risk, having repeat CA125/ultrasound (second-line test). CA125 was interpreted using the "Risk of Ovarian Cancer Algorithm" (ROCA). We report on performance of other serial algorithms and a single CA125 threshold as a first-line screen in the UKCTOCS dataset.Experimental Design: 50,083 post-menopausal women who attended 346,806 MMS screens were randomly split into training and validation sets, following stratification into cases (ovarian/tubal/peritoneal cancers) and controls. The two longitudinal algorithms, a new serial algorithm, method of mean trends (MMT) and the parametric empirical Bayes (PEB) were trained in the training set and tested in the blinded validation set and the performance characteristics, including that of a single CA125 threshold, were compared.Results: The area under receiver operator curve (AUC) was significantly higher (P = 0.01) for MMT (0.921) compared with CA125 single threshold (0.884). At a specificity of 89.5%, sensitivities for MMT [86.5%; 95% confidence interval (CI), 78.4-91.9] and PEB (88.5%; 95% CI, 80.6-93.4) were similar to that reported for ROCA (sensitivity 87.1%; specificity 87.6%; AUC 0.915) and significantly higher than the single CA125 threshold (73.1%; 95% CI, 63.6-80.8).Conclusions: These findings from the largest available serial CA125 dataset in the general population provide definitive evidence that longitudinal algorithms are significantly superior to simple cutoff values for ovarian cancer screening. Use of these newer algorithms requires incorporation into a multimodal strategy. The results highlight the importance of incorporating serial change in biomarker levels in cancer screening/early detection strategies. Clin Cancer Res; 24(19); 4726-33. ©2018 AACR.

AB - Purpose: In the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), women in the multimodal (MMS) arm had a serum CA125 test (first-line), with those at increased risk, having repeat CA125/ultrasound (second-line test). CA125 was interpreted using the "Risk of Ovarian Cancer Algorithm" (ROCA). We report on performance of other serial algorithms and a single CA125 threshold as a first-line screen in the UKCTOCS dataset.Experimental Design: 50,083 post-menopausal women who attended 346,806 MMS screens were randomly split into training and validation sets, following stratification into cases (ovarian/tubal/peritoneal cancers) and controls. The two longitudinal algorithms, a new serial algorithm, method of mean trends (MMT) and the parametric empirical Bayes (PEB) were trained in the training set and tested in the blinded validation set and the performance characteristics, including that of a single CA125 threshold, were compared.Results: The area under receiver operator curve (AUC) was significantly higher (P = 0.01) for MMT (0.921) compared with CA125 single threshold (0.884). At a specificity of 89.5%, sensitivities for MMT [86.5%; 95% confidence interval (CI), 78.4-91.9] and PEB (88.5%; 95% CI, 80.6-93.4) were similar to that reported for ROCA (sensitivity 87.1%; specificity 87.6%; AUC 0.915) and significantly higher than the single CA125 threshold (73.1%; 95% CI, 63.6-80.8).Conclusions: These findings from the largest available serial CA125 dataset in the general population provide definitive evidence that longitudinal algorithms are significantly superior to simple cutoff values for ovarian cancer screening. Use of these newer algorithms requires incorporation into a multimodal strategy. The results highlight the importance of incorporating serial change in biomarker levels in cancer screening/early detection strategies. Clin Cancer Res; 24(19); 4726-33. ©2018 AACR.

KW - Aged

KW - Algorithms

KW - Biomarkers, Tumor/blood

KW - CA-125 Antigen/blood

KW - Early Detection of Cancer

KW - Female

KW - Humans

KW - Longitudinal Studies

KW - Membrane Proteins/blood

KW - Middle Aged

KW - Ovarian Neoplasms/blood

KW - Risk Factors

KW - Ultrasonography

KW - United Kingdom

U2 - 10.1158/1078-0432.CCR-18-0208

DO - 10.1158/1078-0432.CCR-18-0208

M3 - Article

C2 - 30084833

VL - 24

SP - 4726

EP - 4733

JO - Clinical Cancer Research

JF - Clinical Cancer Research

SN - 1078-0432

IS - 19

ER -