Longitudinal Assessment of Labor Market Earnings Among Patients Diagnosed With Cancer in Canada
Bibliographic record
Abstract
Importance: To our knowledge, there have been no studies that estimated the short-, mid-, and long-term effects on cancer survivors' labor market earnings using administrative data. Objective: To estimate the change in labor market earnings due to cancer diagnosis stratified by cancer type and age category. Design, Setting, and Participants: This population-based cohort study used a retrospective analysis of Statistics Canada's administrative linkage file, which includes microdata from the 1991 Census, the Canadian Cancer Registry, mortality records, and personal income tax files. Participants included patients newly diagnosed with cancer from 1992 to 2008. All statistical analyses were finished on September 30, 2020. Exposures: Cancer diagnosis using the International Classification of Diseases, Ninth Revision, and the International Classification of Diseases, Tenth Revision. Main Outcomes and Measures: Annual and percent change in labor market earnings. The empirical strategy used a combination of the Mahalanobis distance and propensity score matching method and the difference-in-difference regression method to select a control group similar to the cancer survivors in this study and assess the association of the cancer diagnosis with labor market earnings, respectively. Results: A total of 59 532 patients with cancer and 243 446 patients without cancer were included in the main analysis. The mean (SD) age was similar between the matched treatment and control cohort (49.70 [8.1] years vs 49.68 [7.2] years), as was the proportion of females (0.49 vs 0.49), and the individual reported income ($37 937 [$18 645] vs $37 396 [$16 876]). The results showed the negative associations of cancer with labor market earnings. Additionally, the severity of the cancer was associated with labor market earnings, where cancer survivors with a severe type of cancer in terms of the 5-year survival rate are shown to have a larger and more persistent earnings difference compared with the control group. Conclusions and Relevance: The findings of this cohort study suggest that labor market earnings losses are associated with a cancer diagnosis. A better understanding of the loss of labor market earnings following cancer diagnosis and by cancer type can play an important role in starting a dialogue in future policy initiatives to mitigate the financial burden faced by cancer survivors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".