'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial

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Standard

'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial. / Røe, Oluf Dimitri; Markaki, Maria; Tsamardinos, Ioannis; Lagani, Vincenzo; Nguyen, Olav Toai Duc; Pedersen, Jesper Holst; Saghir, Zaigham; Ashraf, Haseem Gary.

I: BMJ Open Respiratory Research, Bind 6, Nr. 1, e000512, 2019.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Røe, OD, Markaki, M, Tsamardinos, I, Lagani, V, Nguyen, OTD, Pedersen, JH, Saghir, Z & Ashraf, HG 2019, ''Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial', BMJ Open Respiratory Research, bind 6, nr. 1, e000512. https://doi.org/10.1136/bmjresp-2019-000512

APA

Røe, O. D., Markaki, M., Tsamardinos, I., Lagani, V., Nguyen, O. T. D., Pedersen, J. H., Saghir, Z., & Ashraf, H. G. (2019). 'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial. BMJ Open Respiratory Research, 6(1), [e000512]. https://doi.org/10.1136/bmjresp-2019-000512

Vancouver

Røe OD, Markaki M, Tsamardinos I, Lagani V, Nguyen OTD, Pedersen JH o.a. 'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial. BMJ Open Respiratory Research. 2019;6(1). e000512. https://doi.org/10.1136/bmjresp-2019-000512

Author

Røe, Oluf Dimitri ; Markaki, Maria ; Tsamardinos, Ioannis ; Lagani, Vincenzo ; Nguyen, Olav Toai Duc ; Pedersen, Jesper Holst ; Saghir, Zaigham ; Ashraf, Haseem Gary. / 'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial. I: BMJ Open Respiratory Research. 2019 ; Bind 6, Nr. 1.

Bibtex

@article{49b5bfedfb3d4f388665fe39416457a3,
title = "'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial",
abstract = "Hypothesis We hypothesise that the validated HUNT Lung Cancer Risk Model would perform better than the NLST (USA) and the NELSON (Dutch-Belgian) criteria in the Danish Lung Cancer Screening Trial (DLCST). Methods The DLCST measured only five out of the seven variables included in validated HUNT Lung Cancer Model. Therefore a 'Reduced' model was retrained in the Norwegian HUNT2-cohort using the same statistical methodology as in the original HUNT model but based only on age, pack years, smoking intensity, quit time and body mass index (BMI), adjusted for sex. The model was applied on the DLCST-cohort and contrasted against the NLST and NELSON criteria. Results Among the 4051 smokers in the DLCST with 10 years follow-up, median age was 57.6, BMI 24.75, pack years 33.8, cigarettes per day 20 and most were current smokers. For the same number of individuals selected for screening, the performance of the 'Reduced' HUNT was increased in all metrics compared with both the NLST and the NELSON criteria. In addition, to achieve the same sensitivity, one would need to screen fewer people by the 'Reduced' HUNT model versus using either the NLST or the NELSON criteria (709 vs 918, p=1.02e-11 and 1317 vs 1668, p=2.2e-16, respectively). Conclusions The 'Reduced' HUNT model is superior in predicting lung cancer to both the NLST and NELSON criteria in a cost-effective way. This study supports the use of the HUNT Lung Cancer Model for selection based on risk ranking rather than age, pack year and quit time cut-off values. When we know how to rank personal risk, it will be up to the medical community and lawmakers to decide which risk threshold will be set for screening.",
keywords = "HUNT, lung cancer screening, NELSON, NLST, risk prediction model",
author = "R{\o}e, {Oluf Dimitri} and Maria Markaki and Ioannis Tsamardinos and Vincenzo Lagani and Nguyen, {Olav Toai Duc} and Pedersen, {Jesper Holst} and Zaigham Saghir and Ashraf, {Haseem Gary}",
year = "2019",
doi = "10.1136/bmjresp-2019-000512",
language = "English",
volume = "6",
journal = "B M J Open Respiratory Research",
issn = "2052-4439",
publisher = "B M J Group",
number = "1",

}

RIS

TY - JOUR

T1 - 'Reduced' HUNT model outperforms NLST and NELSON study criteria in predicting lung cancer in the Danish screening trial

AU - Røe, Oluf Dimitri

AU - Markaki, Maria

AU - Tsamardinos, Ioannis

AU - Lagani, Vincenzo

AU - Nguyen, Olav Toai Duc

AU - Pedersen, Jesper Holst

AU - Saghir, Zaigham

AU - Ashraf, Haseem Gary

PY - 2019

Y1 - 2019

N2 - Hypothesis We hypothesise that the validated HUNT Lung Cancer Risk Model would perform better than the NLST (USA) and the NELSON (Dutch-Belgian) criteria in the Danish Lung Cancer Screening Trial (DLCST). Methods The DLCST measured only five out of the seven variables included in validated HUNT Lung Cancer Model. Therefore a 'Reduced' model was retrained in the Norwegian HUNT2-cohort using the same statistical methodology as in the original HUNT model but based only on age, pack years, smoking intensity, quit time and body mass index (BMI), adjusted for sex. The model was applied on the DLCST-cohort and contrasted against the NLST and NELSON criteria. Results Among the 4051 smokers in the DLCST with 10 years follow-up, median age was 57.6, BMI 24.75, pack years 33.8, cigarettes per day 20 and most were current smokers. For the same number of individuals selected for screening, the performance of the 'Reduced' HUNT was increased in all metrics compared with both the NLST and the NELSON criteria. In addition, to achieve the same sensitivity, one would need to screen fewer people by the 'Reduced' HUNT model versus using either the NLST or the NELSON criteria (709 vs 918, p=1.02e-11 and 1317 vs 1668, p=2.2e-16, respectively). Conclusions The 'Reduced' HUNT model is superior in predicting lung cancer to both the NLST and NELSON criteria in a cost-effective way. This study supports the use of the HUNT Lung Cancer Model for selection based on risk ranking rather than age, pack year and quit time cut-off values. When we know how to rank personal risk, it will be up to the medical community and lawmakers to decide which risk threshold will be set for screening.

AB - Hypothesis We hypothesise that the validated HUNT Lung Cancer Risk Model would perform better than the NLST (USA) and the NELSON (Dutch-Belgian) criteria in the Danish Lung Cancer Screening Trial (DLCST). Methods The DLCST measured only five out of the seven variables included in validated HUNT Lung Cancer Model. Therefore a 'Reduced' model was retrained in the Norwegian HUNT2-cohort using the same statistical methodology as in the original HUNT model but based only on age, pack years, smoking intensity, quit time and body mass index (BMI), adjusted for sex. The model was applied on the DLCST-cohort and contrasted against the NLST and NELSON criteria. Results Among the 4051 smokers in the DLCST with 10 years follow-up, median age was 57.6, BMI 24.75, pack years 33.8, cigarettes per day 20 and most were current smokers. For the same number of individuals selected for screening, the performance of the 'Reduced' HUNT was increased in all metrics compared with both the NLST and the NELSON criteria. In addition, to achieve the same sensitivity, one would need to screen fewer people by the 'Reduced' HUNT model versus using either the NLST or the NELSON criteria (709 vs 918, p=1.02e-11 and 1317 vs 1668, p=2.2e-16, respectively). Conclusions The 'Reduced' HUNT model is superior in predicting lung cancer to both the NLST and NELSON criteria in a cost-effective way. This study supports the use of the HUNT Lung Cancer Model for selection based on risk ranking rather than age, pack year and quit time cut-off values. When we know how to rank personal risk, it will be up to the medical community and lawmakers to decide which risk threshold will be set for screening.

KW - HUNT

KW - lung cancer screening

KW - NELSON

KW - NLST

KW - risk prediction model

U2 - 10.1136/bmjresp-2019-000512

DO - 10.1136/bmjresp-2019-000512

M3 - Journal article

C2 - 31803478

AN - SCOPUS:85074901135

VL - 6

JO - B M J Open Respiratory Research

JF - B M J Open Respiratory Research

SN - 2052-4439

IS - 1

M1 - e000512

ER -

ID: 240787266