Process of care failures in women with cervical cancer
Notice bibliographique
Résumé
Background: In the year 2010, approximately 1,300 incident cases of cervical cancer are predicted to have been diagnosed in Canada, making it the 3rd most common cancer among Canadian women between the ages of 20-49 years. There are reliable screening tools, diagnostic tests and effective treatments for pre-invasive lesions and early stage cancers. Thus, theoretically, invasive cervical cancer is a preventable disease. Objective: To assess the quality of health care that women with invasive cervical cancer received within 5 years prior to their diagnosis. The goal was to determine deficiencies in Pap screening and diagnostic and treatment care of pre-invasive lesions of study subjects. Methodology: A case-control study was conducted. Study subjects were long-term residents of Montreal or Laval who were diagnosed with histologically-confirmed primary cervical cancer between January 1, 1998 and December 31, 2004. The identification of cases was done by the Quebec tumour registry and by hospital medical records departments. Cervical screening, diagnostic, and pre-invasive lesion treatment histories were obtained from hospital medical charts, hospital cytology laboratories, subject (or proxy) interviews, and physician questionnaires. The main time window of observation was the interval 5 years before diagnosis but lifetime screening histories were also considered. Processes of care were assessed as per explicit medical review criteria, which were based on clinical practice guidelines and based on consensus by clinical co-investigators. The respondents of the Canadian Community Health Survey (cycle 2.1) and a matched sample of non-cervical cancer cases obtained from the Régie de l'assurance maladie du Québec were used as a comparison group for many analyses. Descriptive statistics and regression modelling techniques were performed to assess associations. Results: A total of 568 women were diagnosed with cervical cancer and met all inclusion criteria. Immigrants (OR 1.40, 95% CI 1.08-1.82), women in common-law relationships (OR 1.62, 95% CI 1.12-2.33), and women who spoke neither French nor English (OR 4.53, 95% CI 2.26-9.07) were at greatest risk of cervical cancer. The majority of cervical cancer cases (whose screening histories could be classified) were screened at least once during their lifetime (90.4%, 95% CI 87.5-93.3) and 9.6% (95% CI 6.7-12.5%) were never screened. Of those women screened in the past, 43.1% (95% CI 38.0-48.2%) were not screened within 5 years of diagnosis. It was found that the greater the time interval since the last Pap, the greater was the risk of cervical cancer. The greatest risk was found for women screened 5 or more years before diagnosis (OR 14.4, 95% CI 9.94-20.91). Cervical cytological abnormalities found by Pap testing were more likely to be appropriately managed in terms of follow-up procedures and timing compared to the follow-up of diagnosed precancerous cervical lesions. Specifically, 12.5% (95% CI 8.7-16.3) of subjects with an abnormal Pap smear and 19.4% (95% CI 13.9-24.9) of subjects with a diagnosed cervical lesion were not followed-up appropriately according to medical criteria. Similarly, 36.7% (95% CI 31.2-42.3) of subjects with an abnormal Pap smear and 52.5% (95% CI 45.5-59.4) of subjects with a cervical lesion were not managed in a timely manner. Conclusion: Most women who were diagnosed with cervical cancer were screened at least once in their lifetimes. However, many women with cervical cancer were not screened within 5 years of diagnosis. If an abnormal Pap test occurred or a precancerous lesion was diagnosed, the processes of care were found to be acceptable in most instances; however, delays in the implementation of these processes were more common. Poor follow-up of diagnosed cervical lesions was found to be more common than poor follow-up of abnormal Pap tests.
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 | 0,005 | 0,035 |
| 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 | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».