Bias due to non-consent in assisted reproductive treatment cohort studies: consent for disclosure to non-contact research in the Human Fertilisation and Embryology Authority register
Notice bibliographique
Résumé
STUDY QUESTION: Is patient consent to research associated with the distribution of population characteristics and study outcomes in ART cohort studies? SUMMARY ANSWER: The distribution of population characteristics in the patient consent subset differs from that in the non-consent subset and is not fully representative of the general ART population; thus, study results of population subsets requiring patient consent may be subject to bias. WHAT IS KNOWN ALREADY: Non-consent in epidemiological studies may bias study results if the consent subset differs systematically from the non-consent subset and is thus not representative of the full study population. ART cohort datasets may be biased if they require patients to consent to use their data. As an example, from September 2009 onwards, ART patients in the UK have been asked for specific 'consent to disclosure of identifying information' (CD) for research studies. STUDY DESIGN, SIZE, DURATION: This cohort study utilized an anonymized version of the Human Fertilisation and Embryology Authority (HFEA) dataset containing all CD and non-CD autologous ART treatment cycles (n = 819 512) conducted from 2004 to 2018 in the UK. A live birth (LB) subset of 155 986 singletons born during the same period was used to analyse child outcomes. Additionally, an aggregated version of the HFEA dataset was used to explore CD trends by clinic type (National Health Service [NHS], private, or both NHS and privately funded). PARTICIPANTS/MATERIALS, SETTING, METHODS: The dataset containing all gamete cycles was used to explore factors associated with giving CD and to compare LB outcome trends (number of LBs per yearly treatment cycles started) between CD and non-CD cycles. The LB subset was used to compare the birthweight outcomes (low birthweight (LBW = birthweight < 2500 g or otherwise) and macrosomia (birthweight ≥4000 g or otherwise)) between CD and non-CD cycles. Logistic regression models explored the association between CD and population characteristics and the impact of CD on birthweight outcomes over the calendar years. Each regression model was adjusted for potential confounders: for all models (maternal age, ethnicity, previous IVF cycles, previous pregnancies, previous LBs, causes of infertility (tubal, endometriosis, male factor, ovulatory, unknown), and embryo transfer type and stage); for LB and birthweight models (ICSI, elective single embryo transfer, and ovarian stimulation); and additionally for birthweight models (child sex and gestation). MAIN RESULTS AND THE ROLE OF CHANCE: During the study period, CD rates increased from 16% at its inception in 2009 to 64% in 2018. Fewer cycles from older patients (40-44 years old) and ethnic minorities (Black and Asian) gave CD. Cycles with previous ART treatments and LBs had lower rates of giving CD. CD was also associated with LB rates (higher in the CD group) and LBW (slightly more prevalent in the non-CD group). CD rates were consistently higher in NHS-only funded clinics than in clinics with partly or fully private funding. It may be possible to adjust for much of the post-2009 bias by weighting by the probability of inclusion derived from supplementary data. LIMITATIONS, REASONS FOR CAUTION: Important factors not provided or unavailable in the dataset included socio-economic and lifestyle factors. Additionally, the anonymized dataset provided to us had banded/categorized maternal age, gestation, and birthweight variables, possibly limiting our estimates' precision. WIDER IMPLICATIONS OF THE FINDINGS: This study shows that using only consented data in ART observational cohort studies may result in a sample that differs from the non-consented sample and general ART population. Specifically, our results show differences in the distribution of population characteristics, LB, and LBW outcomes between CD and non-CD groups in the UK HFEA ART register dataset. Careful attention is therefore required when analysing and interpreting these and similar cohort data; failure to consider the impact of consent will likely produce misleading results. In the HFEA register, this applies to research studies using CD data (including bespoke data requests and linkage studies) after the introduction of CD in October 2009. A potential solution weighting by the probability of consent is briefly introduced. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by the EU H2020 Marie Sklodowska-Curie Innovative Training Networks (ITN) grant Dohartnet (H2020-MSCA-ITN-2018-812660). The authors have no competing interests to declare. TRIAL REGISTRATION NUMBER: N/A.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,021 | 0,031 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».