Morphological and genetic classification of lung cancer: variation in practice and implications for tailored treatment

Histopathology. 2015 Aug;67(2):216-24. doi: 10.1111/his.12638. Epub 2015 Mar 2.

Abstract

Aims: Tailored therapy of lung cancer requires high-quality pathology. Tumours must be subtyped accurately and material preserved for genetic analysis upon which treatment is increasingly based. There is a presumption that pathologists have risen to this challenge, but the nature and degree of variation in practice and quality are unknown.

Methods and results: We collected detailed information on 1507 consecutive, newly diagnosed patients referred to 19 UK lung cancer units, ranging from district general hospitals to specialist cardiothoracic units. In only four centres were pathologists handling thoracic biopsies enrolled in the thoracic external quality assessment (EQA) scheme. Achievement of a positive diagnosis of malignancy ranged from 53 to 88%. Variation in tumour subtypes was wide, and the proportion of biopsies classified as merely 'non-small-cell lung cancer, not otherwise specified' varied from 3 to 20%, despite almost universal use of immunochemistry. The proportion of tumours tested for epidermal growth factor receptor (EGFR) gene mutation ranged from 12 to 92%.

Conclusions: There is considerable variation in practice among UK pathologists and arguably in the quality of pathology, raising questions about expertise, adherence to guidelines, rigour of EQA and, ultimately, the reliability of the pathology that underpins the management of lung cancer.

Keywords: classification; diagnosis; genetics; lung cancer; tailored therapy.

Publication types

  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Non-Small-Cell Lung* / classification
  • Carcinoma, Non-Small-Cell Lung* / genetics
  • Carcinoma, Non-Small-Cell Lung* / pathology
  • ErbB Receptors / genetics*
  • Humans
  • Immunohistochemistry
  • Lung Neoplasms* / classification
  • Lung Neoplasms* / genetics
  • Lung Neoplasms* / pathology
  • Mutation / physiology
  • Precision Medicine
  • Workload / statistics & numerical data

Substances

  • ErbB Receptors