Sökning: onr:"swepub:oai:DiVA.org:umu-165778" >
Early symptoms and ...
Early symptoms and sensations as predictors of lung cancer : a machine learning multivariate model
-
- Levitsky, Adrian (författare)
- Karolinska Institutet
-
- Pernemalm, Maria (författare)
- Karolinska Institutet
-
- Bernhardson, Britt-Marie (författare)
- Karolinska Institutet
-
visa fler...
-
- Forshed, Jenny (författare)
- Karolinska Institutet
-
- Kölbeck, Karl (författare)
- Karolinska Institutet
-
Olin, Maria (författare)
-
- Henriksson, Roger (författare)
- Umeå universitet,Onkologi
-
- Lehtiö, Janne (författare)
- Karolinska Institutet
-
- Tishelman, Carol (författare)
- Karolinska Institutet
-
- Eriksson, Lars E. (författare)
- Karolinska Institutet
-
visa färre...
-
(creator_code:org_t)
- 2019-11-11
- 2019
- Engelska.
-
Ingår i: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 9
- Relaterad länk:
-
https://doi.org/10.1...
-
visa fler...
-
https://umu.diva-por... (primary) (Raw object)
-
https://www.nature.c...
-
https://urn.kb.se/re...
-
https://doi.org/10.1...
-
http://kipublication...
-
visa färre...
Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas
- Av författaren/redakt...
-
Levitsky, Adrian
-
Pernemalm, Maria
-
Bernhardson, Bri ...
-
Forshed, Jenny
-
Kölbeck, Karl
-
Olin, Maria
-
visa fler...
-
Henriksson, Roge ...
-
Lehtiö, Janne
-
Tishelman, Carol
-
Eriksson, Lars E ...
-
visa färre...
- Om ämnet
-
- MEDICIN OCH HÄLSOVETENSKAP
-
MEDICIN OCH HÄLS ...
-
och Klinisk medicin
-
och Cancer och onkol ...
- Artiklar i publikationen
-
Scientific Repor ...
- Av lärosätet
-
Umeå universitet
-
Karolinska Institutet