Screening for new primary cancers in cancer survivors compared to non-cancer controls: a systematic review and meta-analysis
Bibliographic record
Abstract
PURPOSE: The goal of this study was to synthesize evidence comparing cancer screening receipt between cancer survivors and non-cancer controls by conducting a systematic review and meta-analysis. METHODS: We searched PubMed, EMBASE, and CINAHL databases from inception through April 1, 2010 using search terms related to cancer, survivorship, and cancer screening. Studies were included if they reported a comparison of cancer screening receipt between cancer survivors and non-cancer controls. We performed a meta-analysis on the effect of cancer survivorship on breast, cervical, colorectal, and prostate cancer screening receipt. RESULTS: Our search strategy identified 1,778 titles, of which 20 met our inclusion/exclusion criteria. In our meta-analyses, cancer survivors were more likely to be screened for breast, cervical, colorectal, and prostate cancer than non-cancer controls (pooled odds ratio, 1.27; 95 % CI, 1.19-1.36). We observed significant heterogeneity between studies, most of which remained unexplained after subgroup and sensitivity analyses. Important contextual factors, such as how screening programs operate, were not reported in the primary literature. Many cancer survivors (along with non-cancer controls) still did not receive cancer screening. CONCLUSION: Compared with non-cancer controls, cancer survivors receive more frequent screening for new primary breast, cervical, colorectal, and prostate cancers. Future research should seek to determine whether increased uptake of cancer screening is associated with improved outcomes during cancer survivorship. IMPLICATIONS FOR CANCER SURVIVORS: Our systematic review and meta-analysis demonstrated that cancer survivors received more frequent screening for second primary breast, cervical, colorectal, and prostate cancers than non-cancer controls. As many cancer survivors are at an increased risk of developing a second primary cancer, future research should seek to determine whether this increased uptake of cancer screening in cancer survivors leads to improved outcomes during cancer survivorship.
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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 | 0.023 | 0.061 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.046 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".