Up-to-date monitoring of long-term survival is an important task of population-based cancer registries. Period analysis, a new method of survival analysis introduced a few years ago, has been shown to be particularly useful for that purpose. The "classical" period analysis uses a life-table approach which requires both the year and month of diagnosis for implementation in pertinent software programs. However, an increasing number of cancer registries remove the month of diagnosis from their datasets, mainly to ensure the highest possible protection against re-identification of patients. In this paper, we present modifications of period analysis that allow the application of this technique, while almost completely preserving its advantages, in datasets without the month of diagnosis. The modified techniques are illustrated and evaluated using examples from the Surveillance, Epidemiology, and End Results (SEER) programme of the United States (US) National Cancer Institute (NCI), which also has removed month of diagnosis from its most recently released public use database.