A FORMULA FOR PREDICTING THE TUMOR-INCIDENCE IN INTRAPERITONEAL EXPERIMENTS WITH MINERAL FIBERS

We present the results of a statistical analysis based on 175 intraper itoneal fiber experiments coming from numerous reports, published and internal as well. The reference, geometry and chemical composition of each fiber, number of exposed animals, injected quantities, and result ing observed tumors have been recorded in a single database. Following a logistic regression model, we show that the predicted number of tum ors matches in most cases the observed number at an acceptable precisi on level. The formula includes fiber biosolubility, length, diameter, and injected mass in place of number of fibers, which would achieve le ss reliable results with this database. To represent the chemical comp osition, the dissolution coefficient at pH 7.4 is used; a chemical ind ex, such as KI, developed in Germany (TRGS, 1994), could have been use d but it doer not apply to natural fibers and so would have limited th e size of the database. Moreover, the KI index and the K-dis dissoluti on coefficient are known to be closely related within synthetic fibers . A slight adaptation of the model allows one to classify any fiber ex periment in at least two distinct categories reflecting some tumor inc idence level (e.g. higher or lower than 10%), given the experiment par ameters. We notice that a 10% tumor incidence cutpoint as proposed ear lier (Pott et al., 1990) allows a reliable classification of fiber exp eriments, and that a 25% cutpoint is not as reliable.