Screening for Cervical Cancer: A Comprehensive Review of Guidelines
Bibliographic record
Abstract
Cervical cancer remains one of the main causes of female mortality, especially in middle- and low-income countries, despite efforts towards the implementation of global vaccination against human papillomavirus (HPV). The aim of this study was to review and compare the most recently published international guidelines providing recommendations on cervical cancer screening strategies among average and high-risk women. Thus, a comparative review of guidelines by the US Preventive Services Task Force (USPSTF), the American Cancer Society (ACS), the American Society of Clinical Oncology (ASCO), the World Health Organization (WHO), the Canadian Task Force on Preventive Health Care (CTFPHC), the Cancer Council Australia (CCA), and the European Guidelines (EG) was conducted. There is an overall agreement regarding the suggestions made for women younger than 21 and those older than 65, with all guidelines stating against routine screening, with the exceptions of CTFPHC and CCA that expand the age group to up to 70 and 75 years, respectively. Continuation of screening in older women is also suggested in those with a history of a precancerous lesion and those with inadequate screening. Most guidelines recommend routine screening at 30-65 years, while the WHO advises that screening should be prioritized at 30-49 years. HPV DNA testing is the method of choice recommended by most guidelines, followed by cytology as an alternative, except for CTFPHC, which refers to cytology only, with self-sampling being an acceptable method by most medical societies. Agreements exist regarding recommendations for specific groups, such as women with a history of total hysterectomy for benign reasons, women with a complete vaccination against HPV, individuals from the lesbian, gay, bisexual, transgender, and queer communities and women with multiple sexual partners or early initiation of sexual activity. On the other hand, the age group of 21-29 is addressed differently by the reviewed guidelines, while differentiations also occur in the screening strategies in cases of abnormal screening results, in women with immunodeficiency, those with in utero exposure to diethylstilbestrole and pregnant women. The development of consistent practice protocols for the most appropriate cervical cancer screening programs seems to be of major importance to reduce mortality rates and safely guide everyday clinical practice.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".