• 2018-07
  • 2018-10
  • 2018-11
  • Denmark has a long history of establishing nationwide


    Denmark has a long history of establishing nationwide health care registries and databases with information on all Danish residents (Thygesen and Ersbøll, 2014). Two of the nationwide registries with the highest data quality, the Danish Prescription Registry (initiated in 1995 (Kildemoes et al., 2011)) and the Danish Cancer Registry (established in 1943 (Gjerstorff, 2011)), hold virtually complete data on drug prescriptions and incident cancer cases and thus provide a unique setting for active surveillance of cancer risk associated with the use of prescription drugs.
    Setting and Data Sources
    Initial Screening Process
    Evaluation of Signals
    Results Following exclusions, the final study population consisted of 278,485 incident cancer cases. The most frequent cancers were ductal adenocarcinoma of the breast among females (n=36,805), prostate adenocarcinoma among men (n=34,443), and colon adenocarcinoma in both genders (n=24,557). In the initial screening process, 22,125 drug–cancer pairs underwent evaluation. For the majority of cancer types (61 of 99), more than 100 drug–cancer pairs underwent evaluation. A total of 4561 signals (i.e., drug–cancer pairs meeting criteria for strength of association) were identified in the initial screening process, most frequently for cancers of the lung (196 signals for squamous cell carcinoma, 178 for small cell carcinoma and 176 for other adenocarcinomas). For five of the 99 cancer types, we found no signals in the initial screening process (Table 1). Of the signals identified in the initial screening stage, 3464 (75.9%) failed to meet the criteria for dose–response relationship, 12 (0.2%) failed the test for outcome specificity, while 65 (1.4%) failed both criteria; thus leaving 1020 signals. The signals most commonly disqualified because of the specificity criterion were drug–cancer pairs involving squamous cell carcinoma of the notch pathway and various types of lung cancer. An overview of the total number of cases, drug–cancer pairs undergoing evaluation, and final signals are displayed in Table 1. Table 2 displays all signals indicating a reduced cancer risk associated with long-term use of a drug class (on second ATC level), among associations based on more than 100 exposed cases or 1000 exposed controls. Table 3 displays signals suggesting an increased risk with a similar restriction. The full list of all 1020 signals for drug classes at the second or fourth level of the ATC-system and for single drug substances are provided in Supplementary Results I–II, III–IV, and V–VI, respectively.
    Discussion The primary strength of our study is the use of the Danish nationwide health registries, ensuring a prescription history of up to 17years and virtually complete ascertainment of cancer cases. The large study population also allowed evaluation of drug exposure in relation to risk of more rare cancers. The quality of the data in the Danish Prescription Registry (Kildemoes et al., 2011) and the Danish Cancer Registry (Gjerstorff, 2011) has been found to be high (Kildemoes et al., 2011; Gjerstorff, 2011; Statens Serum Institute and Danish Cancer Society, n.d.). Lastly, the detailed stratification according to cancer histology avoided lumping of cancer types with markedly different histology. For example, lung cancer consists of squamous cell carcinoma, adenocarcinoma, small cell carcinoma, large cell carcinoma and carcinoids, among others. As these cancer subtypes have markedly different biology, it is unlikely that their development would be similarly affected by the same drugs. Under the null hypotheses and with the traditional α of 0.05, evaluation of 22,000 associations is expected to result in approximately 1100 false positive associations. Importantly, this pertains to the initial signals (n=4561) before dose–response and specificity requirements. One way to handle this would be to adjust for multiple testing, e.g. Bonferroni correction (Rice et al., 2008). Although such adjustment reduces the number of false positive associations, it also reduces the likelihood that a true association will be captured. Given the explorative nature of our screening study, we should not reject signals before they can be subjected to rigorous evaluation. Thus, we did not include any correction for multiple testing, as also recommended by others (Rothman, 1990).