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Early symptoms and ...
Early symptoms and sensations as predictors of lung cancer : a machine learning multivariate model
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- Levitsky, Adrian (author)
- Karolinska Institutet
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- Pernemalm, Maria (author)
- Karolinska Institutet
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- Bernhardson, Britt-Marie (author)
- Karolinska Institutet
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- Forshed, Jenny (author)
- Karolinska Institutet
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- Kölbeck, Karl (author)
- Karolinska Institutet
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Olin, Maria (author)
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- Henriksson, Roger (author)
- Umeå universitet,Onkologi
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- Lehtiö, Janne (author)
- Karolinska Institutet
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- Tishelman, Carol (author)
- Karolinska Institutet
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- Eriksson, Lars E. (author)
- Karolinska Institutet
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(creator_code:org_t)
- 2019-11-11
- 2019
- English.
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 9
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Abstract
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- The aim of this study was to identify a combination of early predictive symptoms/sensations attributable to primary lung cancer (LC). An interactive e-questionnaire comprised of pre-diagnostic descriptors of first symptoms/sensations was administered to patients referred for suspected LC. Respondents were included in the present analysis only if they later received a primary LC diagnosis or had no cancer; and inclusion of each descriptor required >= 4 observations. Fully-completed data from 506/670 individuals later diagnosed with primary LC (n = 311) or no cancer (n = 195) were modelled with orthogonal projections to latent structures (OPLS). After analysing 145/285 descriptors, meeting inclusion criteria, through randomised seven-fold cross-validation (six-fold training set: n = 433; test set: n = 73), 63 provided best LC prediction. The most-significant LC-positive descriptors included a cough that varied over the day, back pain/aches/discomfort, early satiety, appetite loss, and having less strength. Upon combining the descriptors with the background variables current smoking, a cold/flu or pneumonia within the past two years, female sex, older age, a history of COPD (positive LC-association); antibiotics within the past two years, and a history of pneumonia (negative LC-association); the resulting 70-variable model had accurate cross-validated test set performance: area under the ROC curve = 0.767 (descriptors only: 0.736/background predictors only: 0.652), sensitivity = 84.8% (73.9/76.1%, respectively), specificity = 55.6% (66.7/51.9%, respectively). In conclusion, accurate prediction of LC was found through 63 early symptoms/sensations and seven background factors. Further research and precision in this model may lead to a tool for referral and LC diagnostic decision-making.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
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- ref (subject category)
- art (subject category)
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- By the author/editor
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Levitsky, Adrian
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Pernemalm, Maria
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Bernhardson, Bri ...
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Forshed, Jenny
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Kölbeck, Karl
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Olin, Maria
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show more...
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Henriksson, Roge ...
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Lehtiö, Janne
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Tishelman, Carol
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Eriksson, Lars E ...
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show less...
- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Cancer and Oncol ...
- Articles in the publication
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Scientific Repor ...
- By the university
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Umeå University
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Karolinska Institutet