Increase and Plateauing of Testicular Cancer Incidence in Austria—A Time Trend Analysis of the Past Four Decades
Bibliographic record
Abstract
Background: Testicular germ cell tumors (TGCTs) are the most common malignant tumors in young men. Despite considerable geographic, ethnic, and temporal variations in the incidence of TGCTs, without convincing explanation, incidence rates of TGCTs have been increasing in many countries since, at least, the mid-20th century. Objective: To investigate the incidence rates of TGCTs in Austria by analyzing data from the Austrian Cancer Registry. Design setting and participants: Available data between 1983 and 2018 were provided by the Austrian National Cancer Registry and analyzed retrospectively. Outcome measurements and statistical analysis: Germ cell tumors derived from germ cell neoplasia in situ were classified into seminomas and nonseminomas. Age-specific incidence rates and age-standardized rates were calculated. Annual percent changes (APCs) and average annual percent changes in incidence rates were determined to describe trends from 1983 to 2018. All statistical analyses were performed using SAS version 9.4 and joinpoint. Results and limitations: < 0.0001) from 4.1 (3.4, 4.8) per 100 000 in 1983 to 8.7 (7.9, 9.6) per 100 000 in 2018 by an average APC of 1.74 (1.20, 2.29). The joinpoint regression revealed a change point in time trend in 1995 with an APC of 4.24 (2.77, 5.72) before 1995 and an APC of 0.47 (0.06, 0.89) thereafter. Incidence rates were about twice as high for seminomas as for nonseminomas. A trend analysis by age group showed that the highest TGCT incidence rate was observed among men aged 30-40 yr, with a steep increase before 1995. Conclusions: The incidence rate of TGCTs increased in Austria over the past decades and appears to have reached a plateau at a high level. A time trend analysis by age group for the overall incidence was highest in men aged 30-40 yr, with a steep increase before 1995. These data should lead to awareness campaigns and research to further investigate the causes of this development. Patient summary: We reviewed the data between 1983 and 2018 provided by the Austrian National Cancer Registry to analyze the incidence and incidence trend in testicular cancer. Testicular cancer shows an increasing incidence in Austria. The overall incidence was highest in men aged 30-40 yr, with a steep increase before 1995. The incidence appears to have reached a plateau at a high level in recent years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".