Prediction of dyspnoea following lung resection for cancer

Lafferty, Brian Daniel (2022) Prediction of dyspnoea following lung resection for cancer. MD thesis, University of Glasgow.

Abstract

Lung cancer is the leading cause of cancer death in the UK, with a high incidence in Scotland. In suitable cases surgical resection is the first-choice treatment but is associated with high rates of post-operative morbidity and mortality.

Survival with a meaningful quality of life is important. Public engagement work by our research group has demonstrated that second only to “being alive and cancer free,” exercise capacity was the main priority of patients. However, prediction of post-operative dyspnoea is often difficult and inaccurate. Conventional prediction relies on estimation of function and quantity of lung remaining following surgery. The British Thoracic Society and the National Institute of Clinical Excellence recommend pulmonary function testing and calculation of predicted postoperative FEV1% (ppoFEV1%) and DLCO% (ppoDLCO%), with <40% in either domain being considered ‘high risk’ for post-operative dyspnoea. Whilst these calculations correlate well with post-operative pulmonary function they are not well associated with functional outcomes. No effective method exists for identifying risk of, nor therapeutic strategies to prevent, post-operative dyspnoea.

The British Thoracic Society, The European Society of Thoracic Surgeons and the National Institute of Clinical Excellence highlight the need for studies concerning patient fitness and operative risk when assessing patient suitability lung resection. Furthermore, the James Lind Alliance identified “improving recovery from surgery for elderly patients” as a top 10 priority.

The aim of this thesis was to improve conventional prediction of post-operative dyspnoea. Pilot data from our research group demonstrated association between B-Type natriuretic peptide and both; post-operative cardiac dysfunction and postoperative dyspnoea. The author proposes a novel scoring tool incorporating B-Type natriuretic peptide alongside conventional measurements.

B-Type natriuretic peptide is a quantitative biomarker of myocardial dysfunction, identifying patients at risk of cardiopulmonary complications in a variety of surgeries. Current international guidelines recommend using B-Type natriuretic peptide to aid prognostication of peri-operative morbidity in high-risk patients prior to non-cardiac surgery, yet its potential role in peri-operative decision making in lung resection is unclear. No previous work has compared B-Type natriuretic peptide to functional outcomes following lung resection.

The first investigation of this thesis (chapter 8) explores conventional risk prediction methods in a single site derivation population of 93 patients at the Golden Jubilee National Hospital. Results highlighted poor performance of conventional methods to predict post-operative dyspnoea, confirming the sole use of pulmonary function in this setting could be improved.

In response to these findings, new models were explored (Chapter 9). Univariate analysis identified risk predictors for candidates with and without post-operative dyspnoea. Variables with significance were used to derive new predictive models, incorporating B-Type natriuretic peptide. New models improved prediction within the internal dataset.

An external dataset from three other UK sites was used in an attempt to validate these new models (Chapter 10). Conventional and new models performed similarly within the external population, highlighting the challenge of creating a new scoring tool. Although B-Type natriuretic peptide did not improve risk prediction in either the internal or external dataset, the analysis highlighted the potential of other variables to predict post-operative dyspnoea, such as body mass index, diabetes status and pre-operative pain and quality of life scores.

Secondary analyses demonstrated post-operative B-Type natriuretic peptide was greater in those with increasing post-operative morbidity (>1 complication), those with new post-operative atrial fibrillation and those with pulmonary complications (Chapter 11). A positive association between post-operative BNP and length of hospital stay was also demonstrated. Lung function testing displayed an association with post-operative outcome when used as a continuous variable. There also existed an association between pre-operative quality of life, preoperative performance status and pre-operative ASA which has not been shown before in this population. These positive findings could be useful in the preoperative setting when planning surgery in a shared decision setting.

The work within this thesis confirms current risk prediction methods must be improved, but also highlights the challenges involved in creating scoring tools for use in clinical practice. Future work in this area may involve low technology testing such as heart rate recovery, in addition to the independent predictors of post-operative dyspnoea discovered here, to improve prediction of dyspnoea following lung resection surgery.

• Item Type: Thesis (MD)
• Qualification Level: Doctoral
• Subjects: R Medicine > RC Internal medicine > RC0254 Neoplasms. Tumors. Oncology (including Cancer); R Medicine > RD Surgery
• Colleges/Schools: College of Medical Veterinary and Life Sciences
• Supervisor's Name: Shelley, Dr. Benjamin and McCall, Dr. Philip
• Date of Award: 2022
• Depositing User: Theses Team
• Unique ID: glathesis:2022-83049
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 27 Jul 2022 15:01
• Last Modified: 27 Jul 2022 15:09
• Thesis DOI: 10.5525/gla.thesis.83049
• URI: https://theses.gla.ac.uk/id/eprint/83049