Surgical decision making in upper aerodigestive tract cancer patient follow-up.

Katherine S. Virgo, Randal C. Paniello, Michael H. Johnson, Marc F. Clemente, Frank E. Johnson

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

The objective was to analyze the impact of clinical beliefs on surgical decision making in the posttreatment follow-up of patients with upper aerodigestive tract cancer. Clinical beliefs, defined as perceived benefits and risks of surveillance, were examined. All 824 members of the Society of Head and Neck Surgeons (SHNS) and 522 members of the American Society for Head and Neck Surgery, who were not SHNS members, were surveyed using TNM stage-specific clinical vignettes to measure surgical decision making in the posttreatment follow-up of patients with upper aerodigestive tract cancer. Controlling for physician demographic and practice characteristics, the relationship between clinical beliefs and diagnostic test ordering practices of surgeons was examined using Poisson and negative binomial regression analysis. Age 50 and over and South Central U.S. practice location were significant predictors of the frequency of surveillance testing in at least three TNM stage I models as was the clinical belief that no survival benefit results from the follow-up of patients with TNM stage I cancers. Less than 15% of the variability in follow-up intensity was explained by the TNM stage I models. Predictive ability was substantially improved for the TNM stage II-IV models by including lower TNM stage practice patterns as an independent variable. Most models predicted at least 50% of the variation in follow-up testing. The two clinical beliefs with the greatest impact on surgical decision making in the posttreatment follow-up of patients with upper aerodigestive tract cancer are that surveillance: i) permits palliative treatment and improves quality of life and ii) provides no survival benefit for patients with TNM stage I cancers. Knowledge of lower TNM stage practice patterns can be used to further improve predictive ability for higher stage models.

Original languageEnglish
Pages (from-to)1101-1109
Number of pages9
JournalInternational journal of oncology
Volume21
Issue number5
DOIs
StatePublished - Nov 2002
Externally publishedYes

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