A Practical Approach, Second Edition=Ronald D. Ho.pdf

822 DEVELOPMENTAL REPRODUCTIVE TOXICOLOGY: A PRACTICAL APPROACH, SECOND EDITIONThe control pregnancy for a case of spontaneous abortion is an intrauterine pregnancy that did notmiscarry, but it can end as an induced abortion, a preterm infant, a malformed infant, a stillbirth,etc. If normal surviving infants are used as controls, all factors associated with other types ofreproductive outcome will appear as risk factors for spontaneous abortions, and studies based onsuch comparisons are invalid.Similarly, the appropriate control for a case with one malformation (e.g., isolated spina bifida)is a nonmalformed infant, while the control for a case with two or more malformations can beeither a normal infant or an infant with one malformation. The suitable control for an infantdeveloping mental retardation or childhood cancer is an infant alive at the time of diagnosis butwithout these characteristics. If dead, the control could not have received the diagnosis under study!If, for example, the birth weight distribution of infants developing mental retardation is comparedwith that of all infants born, very low birth weight will appear as a protective factor for mentalretardation. In a way it is, because the risk of death is high and a perinatally dead infant cannotdevelop mental retardation. But if adequate controls are selected (surviving infants), one finds thatvery low birth weight is a risk factor for mental retardation.D. Selection of ControlsIn principle there are two ways to select a control: randomly or by matching. The random controlis drawn by a randomization process, e.g., from a registry of all births or a subset of that registry.If no registries are available, some other type of randomization must be applied.For control matching, one looks for controls that share some characteristics with the case, e.g.,maternal age, parity, or geographical location. Matching can be so-called frequency matching,which means that in the set of controls, the variable in question (e.g., maternal age) occurs withthe same distribution as among the cases. If, for example, 10% of the cases have a maternal agebetween 15 and 19, then 10% of the controls are selected from that maternal age stratum. Thisensures that the cases and controls resemble each other as groups. Individual matching selectscontrols that have the same values as the cases for the matching variables. For example, for aspecific case with a certain maternal age and parity and born at a certain hospital, one or morecontrols are selected with the same or similar (e.g., the same 5-year age group) maternal age andthe same parity, born at the same hospital.The purpose of matching is to reduce the influence of confounding variables (see further on).In other circumstances, matching is more a question of easy control selection. A typical exampleis the “next baby born” control, perhaps with restrictions concerning life or sex. This will give avery heavy matching for date of birth (which is usually not very important) and for hospital ofbirth, but no further matching. This type of control is standard in some registries for congenitalmalformations, but it should be realized that the matching is limited in extent.Matching makes impossible an analysis of the variables for which matching is made. Manyinvestigators therefore prefer to use random controls and control for confounding in other ways(see further on). When some variables are very skewed (e.g., maternal age when the infant hasgastroschisis or Down syndrome), a lack of matching may reduce the information on controlsavailable for extreme groups (very young women in the case of gastroschisis and older women inthe case of Down syndrome), thus reducing power in the analysis. One should remember that thepurpose of the controls is to estimate exposure rate in the population, and if we are interested inexposure rate in very young women (who had infants with gastroschisis), we must use the exposurerate in control women of that age stratum for comparison. If few such women are included in thesample of controls, the estimate of the exposure rate will be uncertain, regardless of the statisticalmethod used.Quite often, one chooses an infant with a congenital malformation (sometimes called a “sickcontrol”) as a control for an infant with another congenital malformation. The beauty of thisapproach is that the estimate of exposure rates may be less biased than when “healthy” controls© 2006 by Taylor & Francis Group, LLC