Descriptive Epidemiology in Cancer Research: A Coordinate System for Cancer Science

Descriptive epidemiology characterizes the distribution of cancer in populations. Its indicators are neither self‐explanatory as facts nor sufficient grounds for causal narratives. Cancer registries, vital statistics, and follow‐up systems make incidence, mortality, survival, and prevalence observable, but these measures depend on how cases, deaths, and populations are defined and recorded. We propose an interpretive coordinate system that locates cancer patterns by person, place, time, complementary indicators, and the processes generating these indicators. This framework characterizes burden, identifies unusual patterns and inequalities, and generates and constrains hypotheses. It examines whether population patterns are compatible with changes in diagnosis, screening, treatment, or policy. It does not by itself establish causation, reveal mechanisms, or estimate intervention effects. Here, we clarify what the principal indicators describe, how they are constructed, and how common overinterpretations can be avoided. We present principles and examples from gastric, thyroid, colorectal, and lung cancer to distinguish observed patterns from competing interpretations, identify additional information needed, and clarify which conclusions remain unjustified. Particular attention is given to denominators, age structure, age‐period‐cohort interpretation, bias, and the assumptions required for comparison and modeling. The aim is to enable cancer researchers to use descriptive epidemiology as a disciplined framework for interpreting population patterns rather than as background statistics or a substitute for causal inference.