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Record W4399676533 · doi:10.1111/ans.19133

It's time to consider screening for anal cancer in high risk populations

2024· article· en· W4399676533 on OpenAlexaboutno aff
Matthew Wei, Justin M Yeung, Ian Faragher

Bibliographic record

VenueANZ Journal of Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsnot available
Fundersnot available
KeywordsAnal cancerMedicinePopulationIncidence (geometry)Men who have sex with menGynecologyCancerInternal medicineHPV infectionObstetricsCervical cancerDemographyImmunologyHuman immunodeficiency virus (HIV)Environmental health

Abstract

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Community groups and medical bodies such as the US Center for Disease Control have called for establishment of screening programs for anal cancer in high-risk groups.1 Over 90% of anal squamous cell carcinoma (aSCC) is caused by human papilloma virus (HPV) infection, particularly serotypes 16 and 18.2 At-risk population groups include HIV-positive men who have sex with men (MSM), transgender women, other HIV-positive individuals, immunocompromised people (e.g., post-transplant) and women with HPV-associated gynaecological cancers.3, 4 The incidence of anal cancer in the general population is 2 per 100 000. The incidence in high-risk groups increases to 10 per 100 000 for transplant patients, 20 per 100 000 for HIV-positive heterosexuals and 100 per 100 000 for HIV positive MSM.5 Indigenous Australians are 1.7 times more likely to be diagnosed with aSCC compared to the wider population.6 Patient risk factors include certain sexual behaviours, such as unprotected receptive intercourse and multiple partners, and smoking.5 More women than men develop anal cancer.3 Women may acquire anal HPV infection by spread from adjacent areas, due to wiping ‘front to back’, a practice encouraged to reduce urinary tract infections.7 aSCC may be preventable through early diagnosis and management of precursor lesions,8 in particular high grade intraepithelial squamous lesions (HSIL). These may be treated with, laser or radiofrequency ablation, or local excision.9 The prospective SPANC trial identified HIV positivity, persistent HPV infection and a previous history of precursor lesions as predictors for developing HSIL.10 The recent ANCHOR multi-center randomized-controlled trial demonstrated a 57% reduction of aSCC in HIV-positive patients who underwent HSIL treatment compared with monitoring alone, highlighting the prophylactic benefits of early diagnosis.8 aSCC has similarities to cervical cancer, which already has established screening programs. The target population for cervical cancer screening is clearly defined – women between 25 and 74. In comparison, it would be difficult to invite high risk individuals to participate in aSCC screening as risk factors (sexuality, HIV status) are often confidential for privacy reasons. Participants would need to self-refer, facilitated by clinician advice. Novel approaches such as embedding aSCC screening for high-risk women within existing cervical screening programs could be considered. Screening for aSCC is already recommended for women with vulval cancer at time of diagnosis.11 The International Anal Neoplasia Society has developed consensus guidelines for screening including risk stratification, age of commencement, screening intervals and resources considerations,4 but many questions remain prior to establishing any aSCC screening program. The optimal screening test and strategy is unclear. Digital anorectal examination (DARE) has been modelled as cost-effective and recommended as normal care for HIV-positive men over 50.12 Anal cytology involves the insertion of a swab into the anal canal. However, this technique has sampling issues, and interpretation of cytology can be challenging. HPV serological testing has therefore been advocated as superior to cytology in aSCC screening.13 High Resolution Anoscopy (HRA) is analogous to colposcopy and takes around 30 minutes. It requires specialized equipment and training and is already utilized to screen selected at-risk patients.14 Routine colonoscopy is currently not indicated. The morbidity and functional considerations of precursor lesion treatment need to be considered. The optimum modality for ablation of precursor lesions is yet to be determined. Further data is required to demonstrate survival benefits of such a programme. Cost-effectiveness has been modelled but is difficult to interpret. Canadian modelling of incorporating aSCC screening into the existing cervical cancer screening reported minor cost savings but no benefit to survival.15 Additional resources would also be required for training personnel to perform more sophisticated HSIL detection techniques such as HRA proficiently. Simple existing public health messages may have some benefit. These include promotion of HPV vaccination, smoking cessation, syringe / needle exchange programs, early diagnosis and treatment for HIV, and advising women to ‘dab’ rather than ‘wipe’. Clinicians will need education to identify high-risk individuals and what investigations and treatments options exist within their communities. Messaging may need to have different strategies targeting specific demographics. Furthermore, medical care has changed significantly, with early use of antiretrovirals now recommended for HIV, decreasing the rate of HPV co-infection.2 HPV vaccination is now readily available in Australia. The anticipated reduction in HPV-associated cancers may take decades to manifest but a reduction in the incidence of genital warts in the adolescent population has already been reported.16 The Australian Technical Advisory Group on Immunization (ATAGI) has recommended HPV vaccination in MSM and immunocompromised people.17 The role of post exposure HPV vaccination in other high-risk groups remains under review. It is time to consider screening programs for at-risk populations to decrease the incidence of aSCC. It is likely that a combination of risk stratification and tests will evolve to select patients for screening. Consultation with stakeholders may lead to a broader coalition to address health equity issues and novel recruitment strategies to facilitate access to a future screening program. Open access publishing facilitated by The University of Melbourne, as part of the Wiley - The University of Melbourne agreement via the Council of Australian University Librarians. Matthew Y Wei: Writing – original draft; writing – review and editing. Justin M Yeung: Supervision; writing – review and editing. Ian G Faragher: Conceptualization; supervision; writing – original draft; writing – review and editing.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.161
GPT teacher head0.430
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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