Preoperative histological classification of primary lung cancer: accuracy of diagnosis and use of the non-small cell category
- 1Department of Pathology, Aberdeen Royal Infirmary and University Medical School, Foresterhill, Aberdeen AB25 2ZD, Scotland, UK
- 2Department of Cardiothoracic Surgery, Aberdeen Royal Infirmary and University Medical School
- Dr Kerr email: Accepted for publication 29 November 1999
Aims—To compare the preoperative classification of lung carcinoma made on cytological and histological specimens with the postoperative classification made on the resected specimen. In addition, to find out how often the term “non-small cell lung cancer, not otherwise specified” (NSCLC) was used, and in such cases to note the final diagnosis.
Methods—Between 1991 and 1995, 303 patients had a lung resection in Aberdeen for primary carcinoma. For each patient, the departmental records were examined for preoperative specimens (cytological and histological). A note was made of whether each specimen was positive or negative for malignancy and, if positive, what the cell type was. Where patients had more than one sample submitted, the most specific result was taken.
Results—Fifty four per cent of patients had a correct specific preoperative diagnosis of malignancy, whereas 34% were labelled as NSCLC. Patients with squamous carcinoma were more likely to have a diagnosis of malignancy (88%) that was specifically correct (75%). Patients who had adenocarcinoma were less likely to have a preoperative diagnosis of malignancy (64%) that was specifically correct (35%). For those in whom a diagnosis of NSCLC was made, 55% turned out to have adenocarcinoma whereas 24% had squamous carcinoma.
Conclusions—By adhering strictly to criteria, a high accuracy of diagnosis can be achieved for squamous carcinoma, but the diagnosis of adenocarcinoma seems to be more of a challenge. NSCLC is a useful and appropriate classification, the use of which reduces the rate of inaccurate specific diagnosis. There are occasions when pathologists can provide a more accurate diagnosis by being less precise.