Degree of coverage and data quality in the Childhood Cancer Registry of Norway

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Degree of coverage and completeness

The Norwegian Childhood Cancer Registry contains all cancer cases registered in children under 15 years of age from 1 January 1985 to 31.12.2022. As of 1 January 2016, adolescents aged 15-17 were included in the registry, but the reporting of clinical assessment and treatment reports is not complete during this transitional period, until new registration forms were introduced from the year of diagnosis 2019. Prevalence and survival are nevertheless complete for the entire age group 0-17 years in the Cancer Registry's basic registry.

The Cancer Registry's basic registry contains information on 98.6 % of all cancer patients (all ages, all diagnoses) in the period 2018-2022. The reports to the Childhood Cancer Registry are good. For leukemia, the completeness is 94.9%, for Hodgkin lymphoma the completeness is 99.9%, for Non-Hodgkin lymphoma the completeness is 99.8% and for CNS completeness is 81.9%. The coverage rate for both assessment and treatment reports for childhood cancer in 2022 is 88.1 %. The degree of coverage for the various hospitals is shown in the annual report. 

Read more about coverage and data quality in the Annual Report 2022 Childhood Cancer (Norwegian only)

Data quality

Quality assurance of data is done as an integral part of the coding and registration process. In addition, the following examples help to ensure data quality in the Cancer Registry:

  • Several independent sources report information
  • The information is reported at several points in the course of the disease
  • The employees have unique expertise in coding cancer cases according to the Cancer Registry's own code book and international coding systems
  • IT systems have rules and barriers for illogical combinations, incorrect information and more
  • The Cancer Registry of Norway conducts analyses and control runs that reveal inconsistency in the data
  • Data extraction for researchers makes it possible to check a smaller data set of information that can reveal individual errors (e.g. incorrect entry of hospital codes) or systematic differences due to different interpretations of coding systems and rules
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