Notice bibliographique
Résumé
When is it appropriate for public health practice to be on the side of an intervention that causes bodily injury? For example, should women with a high genetic risk of breast cancer undergo prophylactic mastectomy? Should tonsillectomies be routinely prescribed to prevent chronic or recurrent acute tonsillitis in children? Should boys be circumcised to protect them from acquiring sexually transmitted diseases (STDs)?1,2 These questions range from the mildly controversial to one of the most intractable questions facing public health practitioners today—namely, the role of male circumcision in curbing HIV transmission in Africa. Few topics touch as raw a nerve as this. Until recently, pediatricians and family physicians in the western world have lived happily with noncommittal guidelines on circumcision, issued by professional societies and intended to inform the physician's dialogue with parents. The decision process was viewed as one in which doctors had the freedom to place their skills at the service of the patients’ best interests, whether these interests stem from religious conviction, family tradition, or health beliefs. This bland tolerance has successfully accommodated a broad range of strong and conflicting opinions. In addition, lest they be accused of overstepping boundaries, practice statements have clearly stipulated that their purview does not extend to male circumcision conducted as religious ritual.3,4 Simply put, it was up to the parents or the consenting-age child to decide after hearing the doctor's views on the procedure. Physicians had only to make sure that they followed sound clinical procedures. Meanwhile, in the background, there has been an emerging knowledge base suggesting health benefits to the circumcised boy in the risk of urinary tract infection, STDs, and even cancer of the penis.5 Even so, with rare exceptions,6 professional societies have carefully avoided to take sides in the polarized debate. Enter the era of acquired immunodeficiency syndrome (AIDS). AIDS has wrought a sense of hopelessness in the public health community as we witness this pandemic evolve in underprivileged areas of the world with little hope of control. It has brought an unparalleled sense of urgency to public health research in seeking promising preventive strategies even before an indisputable body of scientific evidence can be accrued. The urgency has led to bold solutions such as the concept of harm reduction by needle exchange programs and safe injection facilities for illicit drug users in North America and Europe.7,8 Much of the impetus for these interventions has come from compelling observational studies; no randomized, controlled trials have informed these decisions. We can only hope that they will succeed in the long term, rather than leading to unanticipated ill effects—which sometimes happens when, as a society, we apply the precautionary principle. However, implementing these interventions is not a walk in the park, particularly in the United States where legislation has hampered progress.9 There is an ongoing controversy on the benefits of male circumcision in the face of HIV risk,10–13 analogous to the story of needle exchange programs. In both situations, observational studies form the only basis for assessing the validity of the associations. Therein lies the difficulty. It is a daunting job to verify whether a particular behavior or medical intervention truly operates on the etiologic pathway of HIV infection when there are so many confounders along the way. There are many alternative scenarios that are consistent with the observed data. These alternatives need to be shown as implausible before one can establish that male circumcision protects against HIV infection later in life.14 The burden of proof is on the epidemiologist to show that the study design is as free of selection biases as possible, that risk factor information has been measured with the best available instruments, and that careful (even obsessive) statistical analysis has zealously controlled for every possible confounder. Agot and colleagues15 knew this all too well when they set out to conduct yet another observational study on circumcision and HIV risk. How could their study add to the mounting evidence from dozens of ecologic, case-control, and cohort studies that suggest a protective effect for circumcision?16–18 The authors were acutely aware of the difficulty in disentangling the possible biologic effects of circumcision from its inextricable links to religious beliefs, cultural factors, and sexual practices.18 They took great pains to design a study that controlled for the confounding effect of these variables. First, they restricted the survey to a homogeneous group of Kenyan Luo men. Then they recruited these men through a clever sampling scheme that frequency-matched (on geographic proximity) 9 churches from noncircumcising denominations with denominations that preached circumcision. To enhance the comparability, Agot et al.15 restricted the noncircumcising denominations to those favoring polygamy and widow inheritance, as did all 9 circumcising churches. Third, they took into account as pivotal variables in the analysis (1) the churches’ recommendation concerning circumcision, (2) the actual circumcision status of the individual, and (3) an extensive list of empiric confounders at the individual and ecologic level. This highly controlled analysis confirmed a protective effect for circumcision that was convincingly independent from the constellation of factors linked to religion and sexual practices. The study by Agot and colleagues15 is an apt reminder that in our profession, necessity is the mother of invention. In the absence of the opportunity for a randomized intervention trial, many an epidemiologist has had to be creative in designing observational studies that sidestep stubborn biases. By their successful innovation, these researchers have contributed important information to the debate on an urgent public health question. Does this study put an end to the debate? Of course not. However, the quality of the science informing that debate has just moved up a notch. ABOUT THE AUTHOR EDUARDO FRANCO is at McGill University, where he is professor in the Departments of Epidemiology and Oncology, and Director of the Division of Cancer Epidemiology. In his attempts to understand the epidemiology of cancer, human papillomavirus, and HIV infection, he spends a lot of time struggling to disentangle the possible effects of key exposures from inextricably linked confounders. He also worries a lot about measurement error.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».