Preoperative PET may lower unnecessary lung cancer surgeries
Presurgical scanning for metastatic non-small cell lung cancer appears to lower incidence of unnecessary surgeries, according to an analysis published Jan. 21 in the Journal of Nuclear Medicine.
Almost 3,000 veterans with non-small cell lung cancer were followed from 1997 to 2009 to see if preoperative staging with PET improved patient management and cut down on surgeries that ultimately had little benefit. Preliminary results showed that the study was confounded by factors of PET selection, but after a more comprehensive analysis researchers concluded that PET did appear to negate unnecessary operations.
Steven B. Zeliadt, PhD, Health Services Research and Development, Department of Veterans Affairs Medical Center, Seattle, Wash., and colleagues tracked the case management of a total of 2,977 subjects. Of these, 976 underwent resection of their lung cancer. Researchers evaluated the veterans for metastatic disease, mediastinal lymph node involvement and one-year mortality rate.
“PET has now become routine in preoperative staging and treatment planning in the community and appears to be beneficial in avoiding unnecessary surgery,” wrote Zeliadt et al.
Almost one-third (30.3 percent) of subjects were found to have undergone unnecessary surgery. Use of PET skyrocketed from 9 percent to 91 percent during the duration of the study. While the conventional multivariate analyses did not show any significant decrease in unnecessary surgeries due to PET imaging, an addition analysis revealed a more complete picture.
“We anticipated that PET may have been performed selectively on the basis of unobserved characteristics (e.g., providers ordered PET when they suspected disseminated disease),” the authors wrote.
The researchers ended up conducting an additional instrumental variable analysis and concluded that PET did, in fact, lower incidences of unnecessary procedures. The odds ratio was quantified at 0.53. The authors urged other researchers to take care in future analyses to account for similar selection bias.