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Ovarian Cancer Individualized Scoring System Scoring System (OCISS)

9 août 2022 mis à jour par: Sherif Abdelkarim Mohammed Shazly, Assiut University

Ovarian Cancer Individualized Scoring System (OCISS) for Prediction of Ovarian Cancer Prognosis

This project aims at creating an individualized prognostic model using patient characteristics and disease features to determine disease prognosis using machine learning technology. The model can be used to determine the optimal management plan per patient in priori and highlight risk and timing of disease recurrence.

Aperçu de l'étude

Statut

Pas encore de recrutement

Les conditions

Description détaillée

Ovarian cancer (OC) is one of the most common types of malignant tumors and the eighth cause of cancer-related mortality in women.[1] Among gynecological cancers, it is ranked the third following cervical and uterine cancers and is associated with the worst prognosis

[1]. Globally, there are 313,959 new cases and 207,252 deaths of OC annually [1].

Compared to breast cancer, OC is approximately three times more lethal [2]. The high mortality rate of OC is attributed to the capacious anatomical space through which the tumor can grow before it causes significant symptoms, growth of the tumor within abdominal cavity rendering spread of malignant cells widespread and prompt, direct lymphatic drainage to aortic lymph nodes, lack of specific diagnostic symptoms, and unavailability of an efficient screening strategy [3,4]. Symptoms of OC are nonspecific and include vague abdominal pain, abdominal bloating, urinary frequency, early satiety, feeling full, or changes in bowel habits, most of which mimic common gastrointestinal symptoms [5]. Risk factors of OC include obesity, old age, smoking, genetic predisposition, and endometriosis [6,7]. FIGO staging is considered the standard classification system that determines prognosis and management of newly diagnosed OC. However, there are numerous gaps in this staging system that would limit interpretation of clinically relevant data [8]. For instance, the staging system does not consider crucial disease prognostic factors, such as histological type and grade, which are usually considered separately based on available evidence and internal policies. This multi-layer guidance adds to the complexity of decision making. Similarly, personalized management is overlooked since these staging systems do not appreciate individual characteristics such as age, menopausal states, comorbidities, and genetic predisposition. All patients with positive lymph nodes are grouped into a single stage in FIGO staging system, which creates a very diverse group of patients with highly variable survival rates [9]. Management of ovarian cancer is surgical and comprises bilateral sapling-oophorectomy, total abdominal hysterectomy , and infracolic omentectomy. Additional surgical steps and neoadjuvant therapy are potentially determined by disease characteristics. Extent of surgery and neoadjuvant treatment is directly related to postoperative comorbidities and contributes to long term prognosis.

[10]. Therefore, development of an individualized prognostic and decision-making system, based on large multicenter studies, would facilitate accurate prediction of disease prognosis and determination of individualized management strategy.

The study will comprise at least 8 international cancer centers. Data of patients, newly diagnosed with OC between January 2010 and December 2016, will be retrospectively collected. Therefore, a follow-up of at least 5 years would be granted. All women who will be diagnosed with primary ovarian cancer at any stage, of all histological types and grades eligible for the study. All contributing centers should acquire institutional review board (IRB) approval prior to data collection.

Inclusion criteria:

  • Women diagnosed with ovarian cancer between January 2010 and December 2016.
  • Primary non-recurrent diagnosis of ovarian cancer.
  • Women should be diagnosed and managed by the corresponding center.
  • Patients with adequate clinical and pathological data

Exclusion criteria:

  • Inadequate information and follow-up for at least 5 years.
  • Authorization to use anonymous patient data for research purposes. Data will be collected using an excel spreadsheet designed for this study and shared among contributing centers. Data include patients' demographics such as age, parity, body mass index, ethnicity, smoking index, contraception method, menopausal status, medical comorbidities [coronary artery disease, diabetes on insulin, hypertension, chronic renal 3 disease, chronic lung disease, thyroid dysfunction], preoperative imaging [cancer stage, involvement of ovaries, surface involvement, uterine involvement, tubal involvement, inguinal lymph nodes (number, largest diameter), extra abdominal lymph nodes (size and enlargement), abdominal invasion (omental deposits > 2cm, peritoneal carcinomatosis), other pelvic invasion], positive cytology, grade (high/low), pleural effusion and cytology, ascites, performance status, histological type, biomarkers, BRCA I and II (germline or somatic), and serum albumin level. Details of management plan will be collected including treatment approach [Time from diagnosis to surgery, Surgical approach, PA lymphadenectomy (systematic, selective, none)], chemotherapy [systematic or intraperitoneal], and other treatments given.

Treatment outcomes such as complications, debulking success, spill, nodal metastasis, microscopic peritoneal metastasis, microscopic omental metastasis, response to chemotherapy, and CA 125 changes will be included. Data will not include any identifiable information.

Type d'étude

Observationnel

Inscription (Anticipé)

1000

Contacts et emplacements

Cette section fournit les coordonnées de ceux qui mènent l'étude et des informations sur le lieu où cette étude est menée.

Coordonnées de l'étude

Lieux d'étude

      • Alexandria, Egypte, 21516
      • Assiut, Egypte, 71511

Critères de participation

Les chercheurs recherchent des personnes qui correspondent à une certaine description, appelée critères d'éligibilité. Certains exemples de ces critères sont l'état de santé général d'une personne ou des traitements antérieurs.

Critère d'éligibilité

Âges éligibles pour étudier

18 ans à 80 ans (Adulte, Adulte plus âgé)

Accepte les volontaires sains

Non

Sexes éligibles pour l'étude

Femelle

Méthode d'échantillonnage

Échantillon de probabilité

Population étudiée

All women who will be diagnosed with primary ovarian cancer at any stage, of all histological types and grades eligible for the study

La description

Inclusion Criteria:

  • Women diagnosed with ovarian cancer between January 2010 and December 2016.

    • Primary non-recurrent diagnosis of ovarian cancer.
    • Women should be diagnosed and managed by the corresponding center.
    • Patients with adequate clinical and pathological data

Exclusion Criteria:

  • • Inadequate information and follow-up for at least 5 years.

    • Authorization to use anonymous patient data for research purposes.

Plan d'étude

Cette section fournit des détails sur le plan d'étude, y compris la façon dont l'étude est conçue et ce que l'étude mesure.

Comment l'étude est-elle conçue ?

Détails de conception

  • Modèles d'observation: Cohorte
  • Perspectives temporelles: Rétrospective

Que mesure l'étude ?

Principaux critères de jugement

Mesure des résultats
Description de la mesure
Délai
Cancer-specific survival (CSS) rate at 5 years
Délai: Within 5 years after diagnosis of ovarian cancer
Percentage of women newly diagnosed with ovarian cancer who do not die from ovarian cancer after 5 years
Within 5 years after diagnosis of ovarian cancer
Cancer-specific survival (CSS) rate at 3 years
Délai: Within 3 years after diagnosis of ovarian cancer
Percentage of women newly diagnosed with ovarian cancer who do not die from ovarian cancer after 3 years
Within 3 years after diagnosis of ovarian cancer

Mesures de résultats secondaires

Mesure des résultats
Description de la mesure
Délai
Recurrence-free survival (RFS) rate at 5 years
Délai: Within 5 years of diagnosis of ovarian cancer
Percentage of newly diagnosed women who do not experience disease recurrence during follow-up
Within 5 years of diagnosis of ovarian cancer
Recurrence-free survival (RFS) rate at 3 years
Délai: Within 3 years of diagnosis of ovarian cancer
Percentage of newly diagnosed women who do not experience disease recurrence during follow-up
Within 3 years of diagnosis of ovarian cancer

Collaborateurs et enquêteurs

C'est ici que vous trouverez les personnes et les organisations impliquées dans cette étude.

Parrainer

Publications et liens utiles

La personne responsable de la saisie des informations sur l'étude fournit volontairement ces publications. Il peut s'agir de tout ce qui concerne l'étude.

Publications générales

Dates d'enregistrement des études

Ces dates suivent la progression des dossiers d'étude et des soumissions de résultats sommaires à ClinicalTrials.gov. Les dossiers d'étude et les résultats rapportés sont examinés par la Bibliothèque nationale de médecine (NLM) pour s'assurer qu'ils répondent à des normes de contrôle de qualité spécifiques avant d'être publiés sur le site Web public.

Dates principales de l'étude

Début de l'étude (Anticipé)

11 novembre 2022

Achèvement primaire (Anticipé)

11 août 2023

Achèvement de l'étude (Anticipé)

22 novembre 2023

Dates d'inscription aux études

Première soumission

9 août 2022

Première soumission répondant aux critères de contrôle qualité

9 août 2022

Première publication (Réel)

11 août 2022

Mises à jour des dossiers d'étude

Dernière mise à jour publiée (Réel)

11 août 2022

Dernière mise à jour soumise répondant aux critères de contrôle qualité

9 août 2022

Dernière vérification

1 août 2022

Plus d'information

Termes liés à cette étude

Plan pour les données individuelles des participants (IPD)

Prévoyez-vous de partager les données individuelles des participants (DPI) ?

Indécis

Informations sur les médicaments et les dispositifs, documents d'étude

Étudie un produit pharmaceutique réglementé par la FDA américaine

Non

Étudie un produit d'appareil réglementé par la FDA américaine

Non

Ces informations ont été extraites directement du site Web clinicaltrials.gov sans aucune modification. Si vous avez des demandes de modification, de suppression ou de mise à jour des détails de votre étude, veuillez contacter register@clinicaltrials.gov. Dès qu'un changement est mis en œuvre sur clinicaltrials.gov, il sera également mis à jour automatiquement sur notre site Web .

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