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  Vol. 153 No. 3, 8 FEB 1993 TABLE OF CONTENTS
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Application of an Algorithm for Staging Small-cell Lung Cancer Can Save One Third of the Initial Evaluation Costs

Gary E. Richardson, MD; David J. Venzon, PhD; Ruby Phelps; Margaret Edison, RN; Martin Brown, PhD; James N. Frame, MD; Daniel C. Ihde, MD; Bruce E. Johnson, MD

Arch Intern Med. 1993;153(3):329-337.


Abstract

Objective
Design of a cost-effective algorithm for staging disease in patients with small-cell lung cancer.

Design
An algorithm was constructed by analyzing all permutations of a sequence of procedures required to stage disease in patients with small-cell lung cancer. Procedural costs were determined, and the model was applied to the small-cell lung cancer patient population treated at the National Cancer Institute, Bethesda, Md, from 1973 to 1989. The final algorithm was derived from the permutation with the lowest cost per accurately staged patient.

Setting
A single government institute, the National Cancer Institute.

Patients
Four hundred fifty-one patients with previously untreated, consecutive histologically documented small-cell lung cancer entered into therapeutic protocols at the National Cancer Institute from April 1973 through July 1989.

Data were obtained from small-cell lung cancer protocol databases and patients' medical records.

Main Outcome Measure
The cost per patient of each sequence of staging procedures when applied to the patient population.

Results
The least expensive sequence of procedures saved $1418 per patient when compared with application of a standard set of staging procedures to all patients. The major factor in reducing costs was the concept of stopping the staging procedures after a site of distant metastatic disease had been identified.

Conclusions
An algorithm consisting of a set of sequential staging procedures can accurately stage disease in patients with small-cell lung cancer and save more than one third of the costs of an inclusive standard set of staging procedures.

(Arch Intern Med. 1993;153:329-337)



Author Affiliations

From the Navy Medical Oncology Branch (Drs Richardson, Ihde, and Johnson and Mss Phelps and Edison); Biostatistics and Data Management Section (Dr Venzon), Clinical Oncology Program, and the Applied Research Branch, Division of Cancer Prevention and Control (Dr Brown), National Cancer Institute; Department of Medicine, Uniformed Services University of the Health Sciences (Drs Richardson, Frame, Ihde); and National Naval Medical Center (Drs Richardson, Frame, Ide, and Johnson and Mss Phelps and Edison), Bethesda, Md.



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