This chapter presents formulae that methodologically adjust for losses, and gives examples describing magnitude of bias in survival estimates without such adjustment. Loss-adjusted survival is estimated under the assumption that survival of patients Lost to follow-up is the same as that for patients with known follow-up time and similar characteristics of different prognostic factors at first entry. The observed number of Losses to follow-up is then relocated into expected numbers of death and survivors on this basis. Standard methods, such as the actuarial one, are then applied with the sum of observed and expected outcome events. A total of 336 hospital series of treated new breast cancer cases from Mumbai with 24% lost to follow-up revealed a substantial bias of 7 per cent units for 3-year survival estimated with (54%) and without (61%) loss-adjustment. Stepwise adjustment of losses established that increasing the number of prognostic factors explained the bias better. Population-based series comprising 13 371 cases of top ranking cancers from Chennai, with loss to follow-up ranging from 7-24%, revealed negligible bias, ranging from 0-2% in 5-year survival by the loss-adjusted approach for different cancers. Data source seems to affect the need for loss-adjustment, and the loss-adjusted approach is recommended when hospital-based cancer registry data of a low- or medium-resource country are used to evaluate the outcome of cancer patients.