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Symptomatic diagnosis of lung cancer in a population referred to lung-shadow clinic with high rates of chronic respiratory diseases: a feasibility study

Symptomatic diagnosis of lung cancer in a population referred to lung-shadow clinic with high rates of chronic respiratory diseases: a feasibility study
Symptomatic diagnosis of lung cancer in a population referred to lung-shadow clinic with high rates of chronic respiratory diseases: a feasibility study
n the UK, 86% of lung cancer (LC) patients are diagnosed when curative treatment is not possible. Government guidelines recommend urgent chest X-ray referrals for patients presented with any 1 of 10 suggested LC symptoms. Little evidence currently supports these recommendations. Thus, the need for prospective studies to identify the predictive values of symptoms for LC diagnosis.
This study aimed to investigate the feasibility of a prospective study to identify symptoms that predict LC in a secondary care population with high rates of chronic respiratory disease by investigating 1) the content validity and acceptability to this population of a patient-completed questionnaire, and 2) identifying patient-elicited symptoms that predict LC.
The Identifying Symptoms that Predict Chest and Respiratory Disease (IPCARD) questionnaire was used to prospectively collect symptom, risk and comorbidity data in a chest clinic population investigated for LC (Patients aged ?40). LC was identified six months following recruitment. Semi-structured and cognitive interviews explored the acceptability and content validity of the IPCARD questionnaire in this population. Multiple logistic regression was used to identify symptoms independently associated with LC in the clinic population, and in a COPD sub-group; at two levels of entry criteria (p<0.05 and p<0.15).
359 patients (70% of those eligible) completed the IPCARD questionnaire, and 77 (21.4%) were diagnosed with LC. Qualitative research indicated that participants found the IPCARD questionnaire acceptable, and its content validity was established in this secondary care population. Cough and breathing changes first indicated in the last three months, predicted LC in this referred population (p<0.05). In the COPD sub-group, the symptom descriptor, unable to get enough air predicted LC (p<0.05). At the relaxed criteria (p<0.15), five symptoms predicted LC in the full clinic population; a hard/harsh cough without phlegm, increasing chest infections, and weight gain (last 12 months) were added to the previous model. The COPD sub-group at p<0.15, breathing changes experienced (last three months), breathing changes first indicated within the last three months, unable to get enough air, and wheezing sensation, were predictors. Based on the more rigorous entry criteria (p<0.05), the diagnostic criteria for the COPD sub-group (positive likelihood ratio (+LR)=1.91; Area under curve (AUC)=0.739) performed slightly better than the criteria for the full population (+LR=1.49; AUC=0.729) (at optimal cut-off).
The better performance of the COPD–specific model supports the need for an adequately powered study to investigate the predictive values of LC symptoms in homogeneous populations with specific respiratory diseases.
Shim, Joanna
e2666d72-5c28-4fe4-acdc-a740b9beef45
Shim, Joanna
e2666d72-5c28-4fe4-acdc-a740b9beef45
Brindle, Lucy
17158264-2a99-4786-afc0-30990240436c
George, Steve
bdfc752b-f67e-4490-8dc0-99bfaeb046ca

Shim, Joanna (2015) Symptomatic diagnosis of lung cancer in a population referred to lung-shadow clinic with high rates of chronic respiratory diseases: a feasibility study. University of Southampton, Faculty of Health Sciences, Doctoral Thesis, 372pp.

Record type: Thesis (Doctoral)

Abstract

n the UK, 86% of lung cancer (LC) patients are diagnosed when curative treatment is not possible. Government guidelines recommend urgent chest X-ray referrals for patients presented with any 1 of 10 suggested LC symptoms. Little evidence currently supports these recommendations. Thus, the need for prospective studies to identify the predictive values of symptoms for LC diagnosis.
This study aimed to investigate the feasibility of a prospective study to identify symptoms that predict LC in a secondary care population with high rates of chronic respiratory disease by investigating 1) the content validity and acceptability to this population of a patient-completed questionnaire, and 2) identifying patient-elicited symptoms that predict LC.
The Identifying Symptoms that Predict Chest and Respiratory Disease (IPCARD) questionnaire was used to prospectively collect symptom, risk and comorbidity data in a chest clinic population investigated for LC (Patients aged ?40). LC was identified six months following recruitment. Semi-structured and cognitive interviews explored the acceptability and content validity of the IPCARD questionnaire in this population. Multiple logistic regression was used to identify symptoms independently associated with LC in the clinic population, and in a COPD sub-group; at two levels of entry criteria (p<0.05 and p<0.15).
359 patients (70% of those eligible) completed the IPCARD questionnaire, and 77 (21.4%) were diagnosed with LC. Qualitative research indicated that participants found the IPCARD questionnaire acceptable, and its content validity was established in this secondary care population. Cough and breathing changes first indicated in the last three months, predicted LC in this referred population (p<0.05). In the COPD sub-group, the symptom descriptor, unable to get enough air predicted LC (p<0.05). At the relaxed criteria (p<0.15), five symptoms predicted LC in the full clinic population; a hard/harsh cough without phlegm, increasing chest infections, and weight gain (last 12 months) were added to the previous model. The COPD sub-group at p<0.15, breathing changes experienced (last three months), breathing changes first indicated within the last three months, unable to get enough air, and wheezing sensation, were predictors. Based on the more rigorous entry criteria (p<0.05), the diagnostic criteria for the COPD sub-group (positive likelihood ratio (+LR)=1.91; Area under curve (AUC)=0.739) performed slightly better than the criteria for the full population (+LR=1.49; AUC=0.729) (at optimal cut-off).
The better performance of the COPD–specific model supports the need for an adequately powered study to investigate the predictive values of LC symptoms in homogeneous populations with specific respiratory diseases.

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Published date: May 2015
Organisations: University of Southampton, Faculty of Health Sciences

Identifiers

Local EPrints ID: 384345
URI: http://eprints.soton.ac.uk/id/eprint/384345
PURE UUID: ceda048a-1d72-4958-9295-f607d84652b5
ORCID for Lucy Brindle: ORCID iD orcid.org/0000-0002-8933-3754

Catalogue record

Date deposited: 22 Dec 2015 14:39
Last modified: 15 Mar 2024 03:25

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Contributors

Author: Joanna Shim
Thesis advisor: Lucy Brindle ORCID iD
Thesis advisor: Steve George

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