Selective Application of a Test Based on Risk: Using Limited Resources Wisely
Authors: Mark N. Levine, Jim Julian
Journal: Journal of Clinical Oncology (2013)

Accurate staging is important in the clinical management of nasopharyngeal carcinoma (NPC), which is endemic in southern China. The usual staging consists of magnetic resonance imaging of the head and neck followed by conventional imaging (CI) with chest x-ray, bone scan, and abdominal ultrasound to look for distant metastases. The potential for []F-fluorodeoxyglucose (FDG) positron emission tomography and computed tomography (PET-CT) to detect distant metastases in patients with negative CI tests has been reported in other jurisdictions. PET-CT is expensive and likely a limited resource in China. Tang et al describe a diagnostic testing strategy based on an approach that stratifies patients into different risk groups and then applies PET-CT selectively, with the goal of providing the greatest benefit for the most patients. In a prospective cohort study, patients with NPC underwent CI and PET-CT. Any abnormality suspicious for metastases was confirmed by biopsy, additional imaging, or if neither were done, 12 months of metastases-free follow-up. Any patient with a negative battery of tests who developed a distant metastasis within 12 months was considered to have had false-negative imaging tests. Imaging tests were read by experienced physicians without knowledge of the clinical course. The optimal design would have been a randomized trial in which patients with NPC were allocated to CI or CI plus PET-CT, after which an unbiased assessment of the added value of PET-CT to CI could have been obtained. The limitation of the cohort design is that there is no independent reference standard; the tests under study are used to define the outcome. Because PET-CT diagnosed more than twice as many patients with distant metastases as did CI, it is likely that the added value of PET-CT is overestimated. In the cohort of 583 patients, 86 (15%) were found to have distant metastases: 41 by PET-CT alone, one by CI alone, 30 by PET-CT and CI, and 14 by other tests (ie, 71 [83%] by PET-CT and 31 [36%] by CI). The sensitivity, specificity, positive predictive value, and negative predictive value of PET-CT for distant metastases were 83%, 98%, 88%, and 97%, respectively. The corresponding values for CI were 36%, 98%, 80%, and 90%. In developing their case, the investigators focus on “the positive yield” as the number of true-positive cases of the diagnostic test as a proportion of the total number of patients who underwent imaging (ie, 12.2% for PET-CT v 5.3% for CI). They present data to support that both nodal stage and Epstein-Barr virus (EBV) titer are associated with distant metastases, according to the following criteria: presence of N2 or N3 disease, 76% of patients with distant metastases and EBV DNA 4000 copies/mL, 80% with distant metastases. They then use both of these factors to define patient populations with higher prevalence of distant metastases in whom the positive yield with PET-CT is relatively high. For example, in patients with N2 or N3 disease, the positive yield becomes 62% compared with 27% with CI, and in patients with high EBV DNA levels, it is 22% versus 9% with CI. Finally, they combine both nodal status and EBV titer to define three risk groups (very low, low, and intermediate) and show that there is little to be gained over CI by performing PET-CT on the very low risk group. This approach works best when the false-positive fraction is low, but there will likely be a trade-off in terms of an increased falsenegative fraction. In 2006, Journal of Clinical Oncology published an editorial entitled, “Economic Evaluation in the Journal of Clinical Oncology: Past, Present, and Future,” which described a hierarchy of economic analyses from cost minimization (weakest) to cost effectiveness (strongest), as well as the type of economics articles the journal editors would be most interested in. A cost minimization study assumes that the outcomes of two interventions are the same and the difference in the cost of the two alternatives is all that matters. Presumably, the cheapest intervention would be chosen. The weakness with this design is that it ignores the downstream costs of an intervention. In a cost effectiveness study, the costs of both the interventions and what happens to the patient after the intervention are collected for both interventions. The ratio of the difference in costs between therapies divided by the difference in effects (eg, survival) is called the “incremental cost effectiveness ratio.” The economic analysis in the study by Tang can be classified as cost minimization. The costs were incomplete as they were limited to the cost of the imaging tests. The details of all the consequences of the imaging tests and associated costs were lacking (eg, standard therapy for NPC if no distant metastases detected, type of therapy if metastases detected on staging, and extra imaging tests and biopsies required for both true positives and false positives). On the basis of such limitations, care must be taken in making any inferences in terms of any economic advantage of restricting PET-CT to high-prevalence strata. There is no doubt that the economic comparison of CI plus PET-CT versus CI alone is complex. One way of handling such a comparison in an analytic sense would be to begin with a Markov model, which would lay out all the interventions, consequences, and outcomes. Then probabilities and costs are added to the model. JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 31 NUMBER 23 AUGUST 1