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Comments on “compartmental biodistribution of a monoclonal antibody against human lung adenocarcinoma grown in athymic mice”
Nucl. Med. Biol. Vol. 18, No. 3, p. 367, 1991
ing the residual sum of squares. In other words many different sets of pharmacokinetic parameters, in most cases, give about equally good fits of the data, and of course many more not so good fits! The authors put a special emphasis on the identifiability of this and previously considered models, yet no values for the parameters of this model are given and no physiological interpretation thereof is presented. This model was used only as a descriptor of the experimental data, therefore the identifiability of the individual model parameters is immaterial. Almost thirty years ago Bergner (1962) emphasized that experimental data can be used for scientific purposes only if the model used has correlates of meaningful physical parameters, defined u priori. Unfortunately this truth is easily forgotten; widespread availability of rapid computational devices has made elaborate manipulation of data a common practice, with the result that a large number of models appearing in the literature have only descriptive value and do not provide a scientific confirmation to any explicit hypothesis (Rescigno, 1987).
ht. J. Radtat. Appl. Iawum.Part B
6 PcrgamonPmespk 1991. Printed in GreatBritain
0883-2897/91$3.00+ 0.00
Comments on “Compartmental Biodistribution of a Monoclonal Antibody Against Human Lung Adenocarcinoma Grown in Athymic Mice” ALDO RESCIGNO, A. BERTRAND BRILL, HARRY BUSHE and DON. J. HNATOWICH Department of Nuclear Medicine, University of Massachusetts Medical Center, Worcester, MA 01655, U.S.A. Sham et al. (1989) should be complimented for their experimental work on modeling the distribution of the monoclonal antibody KS l/4 in tumor-bearing mice. Some comments though are appropriate with respect to their proposed model. A first impression from Fig. 7 is that the estimated time course of the antibody in blood, tumor, liver and kidneys, does not fit the experimental results reasonably well, as has been suggested by the authors. Indeed, a plot of the residuals (difference between the computed and the measured values) appears to be extremely skewed for all four organs. Even if the fitting of the data was good, this fact by itself would not necessarily prove that a model is correct. It has been shown, for instance, by Lanczos (1956) or more recently by Rescigno and Beck (1987), that in the fitting of a sum of exponential functions it is frequently possible to change substantially the parameter estimates without chang-
References Bergner P. E. E. (1962) The significance of certain tracer kinetical methods, especially with respect to the tracer dynamic definition of metabolic turnover. Acra Radiol. Suppl. 210, 15-60. Lanczos C. (1956) Applied Analysis, Chap. IV, Prentice Hall, Englewood Cliffs, N.J. Rescigno A. and Beck J. S. (1987) The use and abuse of models. J. Pharmacokin. Eiopharm. 15, 327-340. Shani J., Mohd S., Wolf W. and Walker L. E. (1989) Compartmental biodistribution of a monoclonal antibody against human lung adenocarcinoma grown in athymic mice. Nucl. Med. Biol. 16, 33-40.
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ing the residual sum of squares. In other words many different sets of pharmacokinetic parameters, in most cases, give about equally good fits of the data, and of course many more not so good fits! The authors put a special emphasis on the identifiability of this and previously considered models, yet no values for the parameters of this model are given and no physiological interpretation thereof is presented. This model was used only as a descriptor of the experimental data, therefore the identifiability of the individual model parameters is immaterial. Almost thirty years ago Bergner (1962) emphasized that experimental data can be used for scientific purposes only if the model used has correlates of meaningful physical parameters, defined u priori. Unfortunately this truth is easily forgotten; widespread availability of rapid computational devices has made elaborate manipulation of data a common practice, with the result that a large number of models appearing in the literature have only descriptive value and do not provide a scientific confirmation to any explicit hypothesis (Rescigno, 1987).
ht. J. Radtat. Appl. Iawum.Part B
6 PcrgamonPmespk 1991. Printed in GreatBritain
0883-2897/91$3.00+ 0.00
Comments on “Compartmental Biodistribution of a Monoclonal Antibody Against Human Lung Adenocarcinoma Grown in Athymic Mice” ALDO RESCIGNO, A. BERTRAND BRILL, HARRY BUSHE and DON. J. HNATOWICH Department of Nuclear Medicine, University of Massachusetts Medical Center, Worcester, MA 01655, U.S.A. Sham et al. (1989) should be complimented for their experimental work on modeling the distribution of the monoclonal antibody KS l/4 in tumor-bearing mice. Some comments though are appropriate with respect to their proposed model. A first impression from Fig. 7 is that the estimated time course of the antibody in blood, tumor, liver and kidneys, does not fit the experimental results reasonably well, as has been suggested by the authors. Indeed, a plot of the residuals (difference between the computed and the measured values) appears to be extremely skewed for all four organs. Even if the fitting of the data was good, this fact by itself would not necessarily prove that a model is correct. It has been shown, for instance, by Lanczos (1956) or more recently by Rescigno and Beck (1987), that in the fitting of a sum of exponential functions it is frequently possible to change substantially the parameter estimates without chang-
References Bergner P. E. E. (1962) The significance of certain tracer kinetical methods, especially with respect to the tracer dynamic definition of metabolic turnover. Acra Radiol. Suppl. 210, 15-60. Lanczos C. (1956) Applied Analysis, Chap. IV, Prentice Hall, Englewood Cliffs, N.J. Rescigno A. and Beck J. S. (1987) The use and abuse of models. J. Pharmacokin. Eiopharm. 15, 327-340. Shani J., Mohd S., Wolf W. and Walker L. E. (1989) Compartmental biodistribution of a monoclonal antibody against human lung adenocarcinoma grown in athymic mice. Nucl. Med. Biol. 16, 33-40.
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