Radiation Dose Prediction Using Data on Time to Emesis in the Case of Nuclear Terrorism

Abstract Demidenko, E., Williams, B. B. and Swartz, H. M. Radiation Dose Prediction Using Data on Time to Emesis in the Case of Nuclear Terrorism. Radiat. Res. 171, 310–319 (2009). A rigorous statistical analysis of the retrospective estimation of radiation dose received using time to emesis and its uncertainty is provided based on 108 observations associated with accidents with significant exposures to ionizing radiation in the period 1956–2001. The standard error, confidence interval, specificity and sensitivity, and Receiver Operating Characteristic (ROC) curve are used to characterize the uncertainty of the dose prediction. The relative error of the dose prediction using time to emesis data is about 200%. Consequently, if D is the dose assessment, the 95% confidence interval is approximately (D/4, 4D). Our assessment of the precision is applied to computation of the probabilities in triage medical management in the case of a nuclear terrorism event. We also note several factors that indicate that there are additional problems in the use of time to emesis for triage, including a lack of consideration of individuals that do not vomit, differences between the conditions under which the data were obtained and the conditions under which they are likely to be used, and the potential for the incidence of vomiting to be altered by factors unrelated to radiation exposure such as psychogenic factors and the use of emetic agents. In summary, while time to emesis is a rapid and inexpensive method for estimating the radiation dose, it should be used with caution because it is imprecise and may lead to a very high false positive rate. More reliable methods for after-the-fact assessment of radiation dose are needed to complement the use of time to emesis.

[1]  J. Hanley,et al.  The meaning and use of the area under a receiver operating characteristic (ROC) curve. , 1982, Radiology.

[2]  E. Demidenko,et al.  Radiation dose reconstruction from L-band in vivo EPR spectroscopy of intact teeth: Comparison of methods. , 2007, Radiation measurements.

[3]  J. Parker,et al.  ESTIMATING RADIATION DOSE FROM TIME TO EMESIS AND LYMPHOCYTE DEPLETION , 2007, Health physics.

[4]  S. J. Baum,et al.  Symptomatology of acute radiation effects in humans after exposure to doses of 0.5-30 Gy. , 1989, Health physics.

[5]  R. J. Nicolalde,et al.  In Vivo EPR For Dosimetry. , 2007, Radiation measurements.

[6]  C. Metz Basic principles of ROC analysis. , 1978, Seminars in nuclear medicine.

[7]  N. Draper,et al.  Applied Regression Analysis: Draper/Applied Regression Analysis , 1998 .

[8]  Harold M. Swartz,et al.  BiodosEPR-2006 Meeting: Acute dosimetry consensus committee recommendations on biodosimetry applications in events involving uses of radiation by terrorists and radiation accidents , 2007 .

[9]  Ronald E. Goans,et al.  MEDICAL MANAGEMENT OF RADIOLOGICAL CASUALTIES , 2005, Health physics.

[10]  E. Demidenko,et al.  Mixed Models: Theory and Applications (Wiley Series in Probability and Statistics) , 2004 .

[11]  James Armitage,et al.  Medical Management of the Acute Radiation Syndrome: Recommendations of the Strategic National Stockpile Radiation Working Group , 2004, Annals of Internal Medicine.

[12]  S. R. Searle Linear Models , 1971 .

[13]  D. Flynn,et al.  Nuclear terrorism: triage and medical management of radiation and combined-injury casualties. , 2006, The Surgical clinics of North America.

[14]  Stephen W. S. McKeever,et al.  BiodosEPR-2006 consensus committee report on biodosimetric methods to evaluate radiation doses at long times after exposure , 2007 .

[15]  D. Culler,et al.  Comparison of methods , 2000 .

[16]  D. Ruppert,et al.  Measurement Error in Nonlinear Models , 1995 .

[17]  W. Hall,et al.  Confidence Bands for Receiver Operating Characteristic Curves , 1993, Medical decision making : an international journal of the Society for Medical Decision Making.