Human papillomavirus (HPV) vaccination for the prevention of cervical cancer and other HPV-related diseases: a network meta-analysis
Notice bibliographique
Résumé
BACKGROUND: Cervical cancer is the fourth most common cause of cancer-related death amongst females worldwide. Persistent infection with high-risk human papillomavirus (HPV) is the key factor in cervical cancer development. HPV vaccines aim to prevent cancer by generating antibodies against HPV infection. OBJECTIVES: To evaluate the safety and efficacy of HPV vaccines, in females and males, to prevent cervical cancer and other HPV-related diseases, in standard (pairwise) and network meta-analysis (NMA) of randomised controlled trials. SEARCH METHODS: On 10 January 2022, we searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE and Embase. We searched Epistemonikos, ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, the Health Technology Assessment database and vaccine manufacturer websites, and we checked reference lists from other relevant systematic reviews. We applied for Clinical Study Reports (CSRs) from the European Medicines Agency. An update search of electronic databases was done on 18 September 2024. SELECTION CRITERIA: We included randomised controlled trials (RCTs) regardless of language or publication status, assessing HPV vaccines pre-qualified by the World Health Organization (WHO) (Cervarix, Gardasil, Gardasil-9 and Cecolin). DATA COLLECTION AND ANALYSIS: We used methods recommended by Cochrane. We primarily used CSRs to collect data, and we included outcome data irrespective of participants' baseline HPV infection or serostatus. We assessed risk of bias using the Cochrane tool (RoB 2). All outcomes were dichotomous, and we estimated risk ratios (RR) with 95% confidence intervals (CI). We used pairwise analysis for all outcomes. Where data were available, we carried out NMA for critical outcomes for networks in females and males in three age groups, ranking the vaccines using surface under the cumulative ranking curve (SUCRA) and mean ranks. We assessed the certainty of evidence using the GRADE approach. MAIN RESULTS: We included 60 individual studies with 157,414 participants ranging in follow-up from seven months to 11 years. Few participants were under 15. There were no studies for males under 15 years and males over 25 years. We obtained CSRs for 33 of the included studies. We assessed the risk of bias as low to 'some concerns' for the critical outcomes. Cancer and pre-cancer outcomes The studies were not of sufficient duration for cancers to develop. Four studies reported on cancer. No cancers were detected. Critical pre-cancer outcomes were reported in 15- to 25-year-old populations by 11 studies and in > 25-year-old females by three studies with up to seven years follow-up. None were reported in the under 15 years age group. In 15- to 25-year-old females, there was a reduction in CIN2+ irrespective of HPV type after six years (RR 0.70, 95% CI 0.56 to 0.88) (moderate-certainty) and a larger reduction in CIN2+ from vaccine-matched HPV types after six years (RR 0.40, 95% CI 0.30 to 0.54) (moderate-certainty). In females over 25 years old, there was little to no difference between Cervarix and Gardasil compared with control (moderate-certainty). There was no evidence on CIN2+ irrespective of HPV type from studies assessing Cecolin, or from studies assessing different dose schedules. In 15- to 25-year-old females, there was a slight reduction in vaccine-matched HPV-type high-grade vulval (VIN) or vaginal (VaIN) intraepithelial neoplasia following vaccination with Gardasil or Gardasil-9 (moderate-certainty). The NMA found a slight reduction of 1 case per 1000 following Gardasil (RR 0.21, 95% CI 0.1 to 0.45) and 0 cases per 1000 following Gardasil-9 (RR 0.16, 95% CI 0.05 to 0.51). Little to no difference was found in the NMA for Cervarix compared with control (RR 0.28, 95% CI 0.06 to 1.37), or for Cervarix, Gardasil and Gardasil-9 compared to each other. There was a reduction in high-grade anal intraepithelial neoplasia (AIN) irrespective of HPV type in the Gardasil group in one study in men who have sex with men (RR 0.75, 95% CI 0.53 to 1.07) (low-certainty). For both high-grade penile intraepithelial neoplasia (PeIN) irrespective of HPV type and vaccine-matched HPV-type high-grade PeIN, little to no difference per 1000 participants was reported in the Gardasil group in one study with 3880 participants at 36 months follow-up (RR 1.00, 95% CI 0.20 to 4.93) (low-certainty). Serious adverse events In a pairwise analysis of serious adverse events in 39 studies across all vaccine types with 97,272 participants, there was little to no difference in the HPV vaccine groups compared with the control group at up to 72 months follow-up (RR 0.99, 95% CI 0.94 to 1.04) (high-certainty). Treatment rates for HPV-related pre-invasive disease In pairwise analysis of five studies with 38,606 participants, there were 12 fewer people that needed to seek treatment per 1000 participants (95% CI 5 to 17 fewer per 1000) in the HPV vaccine groups compared with the control group rate at up to 84 months follow-up (RR 0.76, 95% CI 0.65 to 0.89) (moderate-certainty). Anogenital warts In pairwise analysis of three studies with 21,271 participants, there were 25 fewer cases of anogenital warts irrespective of HPV type per 1000 participants (95% CI 22 to 28 fewer per 1000) in the HPV vaccine groups compared with the control group rate at up to 48 months follow-up (RR 0.38, 95% CI 0.32 to 0.46) (high-certainty). In the NMA for females 15 to 25 years old, Gardasil-9 was most likely to reduce the risk of developing anogenital warts. AUTHORS' CONCLUSIONS: The evidence in this network meta-analysis of HPV vaccines is based on extensive searches and analyses. There is evidence from randomised controlled trials that HPV vaccination reduces the risk of pre-cancerous outcomes such as CIN2+ and anogenital warts. No data were available for cervical cancer or other cancer outcomes, and no data on pre-cancer outcomes were available for vaccination under age 15 years. There were no safety concerns noted in the studies.
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 | 0,034 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,002 |
| Méta-épidémiologie (sens large) | 0,021 | 0,076 |
| Bibliométrie | 0,007 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
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 ».