The evaluation of epidemiological follow-up studies is frequently based on a comparison of the number O of deaths observed in the cohort from a specified cause with the expected number E calculated from person years in the cohort and mortality rates from a reference population. The ratio SMR = 100 x O/E is called the standardized mortality ratio (SMR). While person years can easily be calculated from the cohort and reference rates are generally available from the national statistical offices or the World Health Organization (WHO), problems can arise with the accessibility of the causes of death of the deceased study participants. However, the information that a person has died may be available, e.g., from population registers. In this paper, a statistical model for this situation is developed to derive a maximum likelihood (ML) estimator for the true (but unknown) number O* of deaths from a specified cause, which uses the known number O of deaths from this cause and the proportion p of all known causes of death among all decreased participants. It is shown that the standardized mortality ratio SMR* based on this estimated number is just SMR* = SMR/p. Easily computable confidence limits can be obtained by dividing the usual confidence limits of the SMR by the opposite limit of the proportion p. However, the confidence level alpha has to be adjusted appropriately.