An application of decision theory to patient screening for an autologous tumour vaccine trial

W. D. Shannon, J. Bryant, Theodore Logan, R. Day

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Patients are eligible for accrual onto a phase I autologous tumour vaccine clinical trial if their resected and dissociated tumour achieves a minimum viable cell count. Because tumour pre-processing and cell count determination are expensive, there has been developed a screening procedure based on tumour mass to screen out those tumours unlikely to yield sufficient viable cells. If θ is the ratio of the expected benefit of an accrual onto the study to the cost of tumour pre-processing and cell counting, then we maximize long-run benefit by pre-processing and counting only those tumours whose masses exceed a cutoff m(c), such that Pr(sufficient tumour cells/mass = m(c)) = 1/θ. We derive algorithms for estimating m(c) and evaluate them under a variety of assumptions concerning the cell count/mass relationship. These include explicit equations for m(c) under parametric assumptions as well as more general algorithms based on non-parametric smoothing techniques. We show that when θ deviates substantially from 2, these methods outperform simple inverse interpolation.

Original languageEnglish (US)
Pages (from-to)2099-2110
Number of pages12
JournalStatistics in Medicine
Volume14
Issue number19
StatePublished - 1995
Externally publishedYes

Fingerprint

Decision Theory
Cancer Vaccines
Vaccine
Screening
Tumor
Neoplasms
Cell
Preprocessing
Cell Count
Count
Counting
Nonparametric Smoothing
Sufficient
Smoothing Techniques
Long-run
Clinical Trials
Exceed
Maximise
Interpolate
Costs and Cost Analysis

ASJC Scopus subject areas

  • Epidemiology

Cite this

An application of decision theory to patient screening for an autologous tumour vaccine trial. / Shannon, W. D.; Bryant, J.; Logan, Theodore; Day, R.

In: Statistics in Medicine, Vol. 14, No. 19, 1995, p. 2099-2110.

Research output: Contribution to journalArticle

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