Ovarian NeoplasmsOVI-DETECTNCT04971421
Liquid Biopsies for Improving the Pre-operative Diagnosis of Ovarian Cancer
An observational study of Ovarian Neoplasms, run by The Netherlands Cancer Institute at 4 sites in Netherlands.
Trial summary
An accurate preoperative diagnosis of an ovarian tumor is important for the patients' surgical work-up, proper referral to oncological centers and for the patients' mental wellbeing since uncertainty about the nature (benign vs malignant) of an ovarian tumor may cause anxiety. Read more about this study
- Who is it for?
- Ages 18 years and older, women onlyHealthy volunteers can take part
- Conditions the study is for
- Ovarian Neoplasms
- What is being tested?
- ctDNA - circulating tumor DNA and TEP - Tumor Educated Platelets
- How many people
- 450 participants
- Where
- 4 sitesNetherlands
- Study dates
- 14 Apr 2021to 1 Oct 2024
- How long will I take part?
- 3 Months
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- Healthy volunteers accepted
- Adult, Older adult
Study population: Women with a suspected malignant ovarian tumor referred to a center for gynecological oncology (CGOA, LUMC or CZE) or one of the four affiliated hospitals (Amphia Ziekenhuis (Breda), HAGA Ziekenhuis (Den Haag), Reinier de Graaf Gasthuis (Delft) of HMC (Den Haag) for surgical treatment.
Who may be able to join
- Age ≥18 years
- Presence of a ovarian tumor and referred to specialized center for surgery based on:
- Any ultrasound model e.g. RMI-scoring model ; IOTA-rules
- Subjective assessment of the referring gynecologist
- Normal Glomerular Filtration Rate (GFR): >60ml/min/1,73m2
- General criteria: a. Understanding of Dutch language b. Fit for surgery (WHO 1-2) c. Written informed consent
Who cannot join
- Suspicion of advanced-stage of disease, e.g. ascites or peritoneal depositions
- History of cancer (excl. BCC) within 5 years prior to inclusion
- Multiple malignancies at the same time
Trial locations and contacts
4 sites in 1 country.
Netherlands4 sites, 4 recruiting
- Recruiting
Dutch Cancer Institute NKI-AVL
Amsterdam
C.A.R. Lok MD,PhD, 0031 20512 2975, c.lok@nki.nl
A. Koch MD,PhD-candidate, 0031 20512 4303, a.koch@nki.nl
- Recruiting
Amsterdam UMC loc VUmc
Amsterdam-Zuidoost
Thomas Wurdinger prof., t.wurdinger@gmail.com
Thomas Wurdinger PhD
- Recruiting
Catharina hospital Eindhoven
Eindhoven
J.M.J. Piek MD,PhD, Jurgen.piek@catharinaziekenhuis.nl
J.M.J. Piek MD,PhD
- Not yet recruiting
Leiden University Medical Center
Leiden
C.D. de Kroon MD,PhD, Cordekroon@lumc.nl
C.D. de Kroon MD,PhD
About this study
Official title: OVI-DETECT Liquid Biopsies for Improving the Pre-operative Diagnosis of Ovarian Cancer
An accurate preoperative diagnosis of an ovarian tumor is important for the patients' surgical work-up, proper referral to oncological centers and for the patients' mental wellbeing since uncertainty about the nature (benign vs malignant) of an ovarian tumor may cause anxiety. Currently, the Risk of Malignancy Index (RMI), with a cut-off value of 200, is often used in the Netherlands to select patients with an increased risk of ovarian cancer that should be referred to an oncologic center. However sensitivity and specificity of the RMI-score are far from optimal. Around 40% of the referred patients have benign disease in final pathological examination. Therefore, other models have been developed, such as the IOTA (International Ovarian Tumor Analysis) consortium algorithms, but these models require training, expertise and are subjective. To determine the nature of an ovarian tumor, histological examination is the golden standard. However, a pre-operative biopsy of an ovarian tumor is undesirable because of the risk of spill of tumor cells in the abdominal cavity. Therefore, there is an urgent need for non-invasive diagnostic tools to determine the nature of an ovarian tumor pre-operatively. Liquid biopsies could be such a non-invasive tool. Currently, circulating tumor DNA (ctDNA) circulating tumor cells (CTC), microRNA (miRNA) and tumor-educated platelets (TEPs) are available and can function as a potential blood-based biosource for (early) cancer diagnostics. Previous studies show promising results of liquid biopsies are used in (early) detection of cancer, also for ovarian cancer.
Therefore, a diagnostic algorithm will be developed using ct-DNA and TEPs as liquid biomarkers in combination with the existing ultrasound models (RMI and IOTA-models) and tumor markers (CA125 and HE4) to differentiate between early ovarian cancer and benign ovarian tumors pre-operatively.
Nature and extent of the burden and risks associated with participation, benefit and group relatedness. There is no extra burden/risk for the patients in this study. Five extra vials of blood will be collected from each participant and two questionnaires will be filled out.
Read the detailed description
In the Netherlands 7600 women are annually diagnosed with an ovarian tumor. Only 5% of these tumors are malignant in the final histology assessment. This means that a general gynecologist is confronted with a patient with low stage ovarian cancer less than once a year. Therefore an accurate preoperative diagnosis of an ovarian tumor is challenging. This accurate pre-operative diagnosis is important because patients with an ovarian carcinoma have to undergo extensive surgery in an oncology center, performed by a gynecologist-oncologist.
The current preoperative possibilities to distinguish benign and malignant ovarian tumors are based on classification systems containing clinical, biochemical and ultrasound characteristics. For example, predictive ultrasound models developed by the IOTA (International Ovarian Tumor Analysis) consortium have been widely used. However, these models require training and expertise and are therefore not always easy to implement. The predictive value of current serum-biomarkers such as CA-125 is limited because this biomarker is not increased in 50% of early stage ovarian carcinoma and CA-125 may also have increased in benign gynecological conditions such as endometriosis.
Current Dutch guidelines make use of the Risk of Malignancy Index (RMI) to determine whether the risk of ovarian carcinoma is increased. This score is based on the concentration of CA125, specific ultrasound characteristics and menopausal status.
According to Dutch guidelines, patients with ovarian tumor are referred to oncology centers if the RMI is increased (>200). The published sensitivity and specificity of RMI in a non-selected population of patients with ovarian tumors is 72% and 92%, respectively. However, the population treated in the oncology centers is enriched with patients with RMI >200. In this selected population, our own prelimenary data show that the sensitivity is 84% for RMI and the specificity is only 51%. This means that the incidence of malignancy within this population is 40%. This is unacceptably low because this implies that half of the patients with benign tumors referred to oncology centers undergo unnecessarily extensive surgery and these patients become unnecessarily emotionally burdened with the possibility of getting cancer.
Tissue biopsies are an important tool in the treatment of ovarian carcinoma because theses procedures can confirm or rule out the presence of a malignancy preoperative. At an early stage, however, tissue biopsy is considered as an unwanted invasive procedure, as this procedure can cause tumor spreading and has an invasive character for patients.
In short, despite the development of numerous prediction models, accurate preoperative diagnosis of early stage ovarian carcinoma is a challenge. There is an urgent need to develop prediction models with a high degree of accuracy that are easy to implement in the clinic to maximize the number of malignant tumors treated in oncology centers.
Blood-based biopsies, 'liquid' biopsies, as an alternative to traditional tissue biopsies, are emerging as these biopsies can provide accurate and comprehensive information on tumors. Examples of such include circulating tumor DNA (ctDNA) circulating tumor cells (CTC) and tumor-educated platelets (TEPs). These platelets are normally responsible for hemostasis, but appear to be able to include tumor signals found in the presence of mirco-tumor RNA. By using whole genome sequencing and detecting structural DNA and RNA changes in the ctDNA and TEPs, malignancies can be detected or excluded. These DNA changes were firstly demonstrated by coincidence when using the NIPT (non-invasive pregnancy test), which, in addition to assessing possible errors in fetal DNA, is also able to detect abnormalities in maternal DNA; in asymptomatic pregnant women, DNA changes were found in maternal DNA accounting for the presence of a malignancy.
Research shows that within patients with early stage ovarian carcinoma (st I and II), ctDNA analysis showed a sensitivity of 69% and a specificity of >99%. The amount of ctDNA correlates with the tumor burden. Other studies conducted within small patient populations show that when ctDNA is combined with existing tumor markers, CA-125 for example, sensitivity and specificity both increase. From prelimanery data on TEP-analysis performed in the NKI-AvL a sensitivity of 76% and specificity of 98% for high-grade ovarian carcinoma was found and a sensitivity of 81% and specificity of 80% for low-grade carcinoma was found.
Therefore, this study investigates the clinical value of longitudinal assessment of liquid biopsy-derived information for preoperative diagnosis in patients suspected of early ovarian cancer
- Conditions
- Ovarian Neoplasms
- Being tested
- ctDNA - circulating tumor DNA, TEP - Tumor Educated Platelets
- Keywords
- Ovarian cancer, tumor educated platelets, circulating tumor DNA, diagnostics
- Medical subject headings
- Ovarian Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
ctDNA - circulating tumor DNADiagnostic test
lcWGS and WGS of circulating tumor DNA
TEP - Tumor Educated PlateletsDiagnostic test
sequencing miRNA from TEPs
| Study group | Role | What they receive |
|---|---|---|
| Benign ovarian tumors | All histological proven benign ovarian tumors Receives: Diagnostic Test: ctDNA - circulating tumor DNA; Diagnostic Test: TEP - Tumor Educated Platelets | |
| Malignant ovarian tumors | All histological proven malignant ovarian tumors Receives: Diagnostic Test: ctDNA - circulating tumor DNA; Diagnostic Test: TEP - Tumor Educated Platelets | |
| Borderline ovarian tumors | All histological proven borderline ovarian tumors Receives: Diagnostic Test: ctDNA - circulating tumor DNA; Diagnostic Test: TEP - Tumor Educated Platelets |
What is being measured
The primary outcome is the main question the study is designed to answer.
The diagnostic accuracy of the developed algorithm
The diagnostic accuracy of the developed algorithm, displayed as sensitivity and specificity.
Measured: 3 -4 years
Secondary outcomes (9)
Cost-effective analysis (I)
The cost effectiveness of the algorithm in the differentiation between (early) OC and benign ovarian tumors will be measured by using different validated questionnaires.
The EQ-5D-5L questionnaire will be used to measure cost-effectiveness modeling, QoL will be measured by means of utilities in order to derive quality adjusted life-years (QALYs). The utilities will reflect the preferences of society for length of life versus quality of life.
Measured: 3 -4 years
Cost-effective analysis (II)
The (Dutch) Medical Consumption Questionnaire (iMCQ) includes questions related to frequently occurring contacts with health care providers. The costs of medical consumption are calculated by multiplying the measured volumes of care by the cost price per unit of care. The higher the score more medical consumption is used.
Measured: 3 -4 years
Cost-effective analysis (III)
The (Dutch) Productivity Cost Questionnaire (iPCQ) will be used to measure the impact of disease on the ability of a person to perform work, either employed or unemployed.
It is divided into 3 categories:
- absences of work measured in days from 0 to 28 days or more, either employed or unemployed;
- the cost of productivity loss for participants and the employees will be calculated by the friction cost method and the human capital method. Higher scores mean more production loss, for employed participants;
- The cost of productivity loss from unpaid work is calculated by multiplying the amount of productivity loss by a standard hourly rate of household care. Higher scores mean more production loss, for unemployed participants;
Measured: 3 -4 years
Psychological Burden (I)
The EQ-5D will be used to measure within five different domains the health status of the patient before and after the surgical intervention and between different ovarian tumor origins. For example a health status can be better, worse or the same. The self-reported visual scale standard, which is part of the EQ-5D, with a value of 80.6 is scored as a normal value for healthy individuals.
Measured: 3 -4 years
Psychological Burden (II)
The EORTC-QLQ-C30 will be used to measure cancer specific cancer-specific quality-of-life, using 5 functional scales, 3 symptom scales, a global health status/quality of life scale, and a number of single items assessing additional symptoms (dyspnea, sleep disturbance, constipation and diarrhea) and perceived financial impact. For ease of presentation and interpretation, all subscale and individual item responses are linearly converted to a 0 to 100 scale. For the functional and global quality of life scales, a higher score represents a better level of functioning. For the symptom scales and items, a higher score reflects a greater degree of symptoms. Individual item responses are linearly converted to a 0 to 100 scale.
The EORTC QLQ-OV28 a 4-point Likert-type response scale is used, ranging from "not at all" to "very much. Results from patients with a benign and malignant ovarian tumor will be compared in the assessment of quality of life.
Measured: 3 -4 years
Psychological Burden (III)
The EORTC QLQ-OV28 a 4-point Likert-type response scale is used, ranging from "not at all" to "very much. Results from patients with a benign and malignant ovarian tumor will be compared in the assessment of quality of life.
Measured: 3 -4 years
Psychological Burden (IV)
The Cancer Worry Scale will be used to assess the worries among the included patients for having ovarian cancer. For all items of the Cancer Worry Scale a 4-point Likert-type response scale is used, ranging from "not at all" to "very much".
Measured: 3 -4 years
Psychological Burden (V)
The Intolerance of Uncertainty Scale (Dutch version IUS-12), will be used to measures both anxious and avoidance components of intolerance of uncertainty. For this study it will be used to measure the coping patients have when faced uncertainty before the final diagnosis is known. It makes use of on 5-point Likert-type response scale is used, ranging from "very strongly disagree" to "very strongly agree".
Measured: 3 -4 years
Psychological Burden (VI)
Decision of regret scale is a 5-point scale to measure the "distress or remorse after a (health) care decision". Participants will be asked to reflect on a specific past decision, and then will be asked to indicate the extent to which they agree or disagree on the regret scale by indicating a number from 1 (Strongly Agree) to 5 (Strongly Disagree) that best indicates their level of agreement. The amount of regret is measured at a point of time when the participant can reflect on the effects of the decision.
This scale will be used to measure the regret patients could have on being referred to an oncological center, independently of the final origin of tumor.
Measured: 3 -4 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Jul 2021
- Study start14 Apr 2021
- Primary completion1 Aug 2024 (estimated)
- Study completion1 Oct 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Ovarian NeoplasmsStudies of the same condition, open and under way.
- More trials run by The Netherlands Cancer InstituteThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case-control
- Time perspective
- Prospective
- Enrolment
- 450 participants (estimated)
- Target duration
- 3 Months
Sponsor and investigators
- Lead sponsor
- The Netherlands Cancer Institute
- Sponsor type
- University, hospital or other
- Collaborators
- Leiden University Medical Center, Catharina Ziekenhuis Eindhoven, Amsterdam UMC, location VUmc, Delft Technical University, Johns Hopkins University, Amphia Hospital, Reinier de Graaf Groep, Haga Hospital, Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
- Responsible party
- Sponsor
- Investigators
- C.A.R. Lok MD, PhD, Principal investigator, Dutch Cancer InstituteC.D. de Kroon, Principal investigator, Leiden University Medical Center / GynecologyJ.M.J. Piek, Principal investigator, Catharina Ziekenhuis Eindhoven / Gy-necology
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04971421
- Sponsor's protocol ID
- NL75690.031.20
- Acronym
- OVI-DETECT
- Status last verified
- Jun 2021
- First submitted
- 17 Feb 2021
- Last updated
- 21 Jul 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 21 Jul 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- OVI-DETECT Liquid Biopsies for Improving the Pre-operative Diagnosis of Ovarian Cancer
- ClinicalTrials.gov ID
- NCT04971421
- Acronym / sponsor ID
- OVI-DETECT / NL75690.031.20
- Conditions
- Ovarian Neoplasms
- Keywords
- Ovarian cancer, tumor educated platelets, circulating tumor DNA, diagnostics
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 450 participants (estimated)
- Lead sponsor
- The Netherlands Cancer InstituteUniversity, hospital or other
- Collaborators
- Leiden University Medical Center, Catharina Ziekenhuis Eindhoven, Amsterdam UMC, location VUmc, Delft Technical University, Johns Hopkins University, Amphia Hospital, Reinier de Graaf Groep, Haga Hospital, Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA)
- Study start
- 14 Apr 2021 (actual)
- Primary completion
- 1 Aug 2024 (estimated)
- Study completion
- 1 Oct 2024 (estimated)
- First posted
- 21 Jul 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
An accurate preoperative diagnosis of an ovarian tumor is important for the patients' surgical work-up, proper referral to oncological centers and for the patients' mental wellbeing since uncertainty about the nature (benign vs malignant) of an ovarian tumor may cause anxiety. Currently, the Risk of Malignancy Index (RMI), with a cut-off value of 200, is often used in the Netherlands to select patients with an increased risk of ovarian cancer that should be referred to an oncologic center. However sensitivity and specificity of the RMI-score are far from optimal. Around 40% of the referred patients have benign disease in final pathological examination. Therefore, other models have been developed, such as the IOTA (International Ovarian Tumor Analysis) consortium algorithms, but these models require training, expertise and are subjective. To determine the nature of an ovarian tumor, histological examination is the golden standard. However, a pre-operative biopsy of an ovarian tumor is undesirable because of the risk of spill of tumor cells in the abdominal cavity. Therefore, there is an urgent need for non-invasive diagnostic tools to determine the nature of an ovarian tumor pre-operatively. Liquid biopsies could be such a non-invasive tool. Currently, circulating tumor DNA (ctDNA) circulating tumor cells (CTC), microRNA (miRNA) and tumor-educated platelets (TEPs) are available and can function as a potential blood-based biosource for (early) cancer diagnostics. Previous studies show promising results of liquid biopsies are used in (early) detection of cancer, also for ovarian cancer.
Therefore, a diagnostic algorithm will be developed using ct-DNA and TEPs as liquid biomarkers in combination with the existing ultrasound models (RMI and IOTA-models) and tumor markers (CA125 and HE4) to differentiate between early ovarian cancer and benign ovarian tumors pre-operatively.
Nature and extent of the burden and risks associated with participation, benefit and group relatedness. There is no extra burden/risk for the patients in this study. Five extra vials of blood will be collected from each participant and two questionnaires will be filled out.
Detailed description
In the Netherlands 7600 women are annually diagnosed with an ovarian tumor. Only 5% of these tumors are malignant in the final histology assessment. This means that a general gynecologist is confronted with a patient with low stage ovarian cancer less than once a year. Therefore an accurate preoperative diagnosis of an ovarian tumor is challenging. This accurate pre-operative diagnosis is important because patients with an ovarian carcinoma have to undergo extensive surgery in an oncology center, performed by a gynecologist-oncologist.
The current preoperative possibilities to distinguish benign and malignant ovarian tumors are based on classification systems containing clinical, biochemical and ultrasound characteristics. For example, predictive ultrasound models developed by the IOTA (International Ovarian Tumor Analysis) consortium have been widely used. However, these models require training and expertise and are therefore not always easy to implement. The predictive value of current serum-biomarkers such as CA-125 is limited because this biomarker is not increased in 50% of early stage ovarian carcinoma and CA-125 may also have increased in benign gynecological conditions such as endometriosis.
Current Dutch guidelines make use of the Risk of Malignancy Index (RMI) to determine whether the risk of ovarian carcinoma is increased. This score is based on the concentration of CA125, specific ultrasound characteristics and menopausal status.
According to Dutch guidelines, patients with ovarian tumor are referred to oncology centers if the RMI is increased (>200). The published sensitivity and specificity of RMI in a non-selected population of patients with ovarian tumors is 72% and 92%, respectively. However, the population treated in the oncology centers is enriched with patients with RMI >200. In this selected population, our own prelimenary data show that the sensitivity is 84% for RMI and the specificity is only 51%. This means that the incidence of malignancy within this population is 40%. This is unacceptably low because this implies that half of the patients with benign tumors referred to oncology centers undergo unnecessarily extensive surgery and these patients become unnecessarily emotionally burdened with the possibility of getting cancer.
Tissue biopsies are an important tool in the treatment of ovarian carcinoma because theses procedures can confirm or rule out the presence of a malignancy preoperative. At an early stage, however, tissue biopsy is considered as an unwanted invasive procedure, as this procedure can cause tumor spreading and has an invasive character for patients.
In short, despite the development of numerous prediction models, accurate preoperative diagnosis of early stage ovarian carcinoma is a challenge. There is an urgent need to develop prediction models with a high degree of accuracy that are easy to implement in the clinic to maximize the number of malignant tumors treated in oncology centers.
Blood-based biopsies, 'liquid' biopsies, as an alternative to traditional tissue biopsies, are emerging as these biopsies can provide accurate and comprehensive information on tumors. Examples of such include circulating tumor DNA (ctDNA) circulating tumor cells (CTC) and tumor-educated platelets (TEPs). These platelets are normally responsible for hemostasis, but appear to be able to include tumor signals found in the presence of mirco-tumor RNA. By using whole genome sequencing and detecting structural DNA and RNA changes in the ctDNA and TEPs, malignancies can be detected or excluded. These DNA changes were firstly demonstrated by coincidence when using the NIPT (non-invasive pregnancy test), which, in addition to assessing possible errors in fetal DNA, is also able to detect abnormalities in maternal DNA; in asymptomatic pregnant women, DNA changes were found in maternal DNA accounting for the presence of a malignancy.
Research shows that within patients with early stage ovarian carcinoma (st I and II), ctDNA analysis showed a sensitivity of 69% and a specificity of >99%. The amount of ctDNA correlates with the tumor burden. Other studies conducted within small patient populations show that when ctDNA is combined with existing tumor markers, CA-125 for example, sensitivity and specificity both increase. From prelimanery data on TEP-analysis performed in the NKI-AvL a sensitivity of 76% and specificity of 98% for high-grade ovarian carcinoma was found and a sensitivity of 81% and specificity of 80% for low-grade carcinoma was found.
Therefore, this study investigates the clinical value of longitudinal assessment of liquid biopsy-derived information for preoperative diagnosis in patients suspected of early ovarian cancer
Study design
- Observational model
- Case-control
- Time perspective
- Prospective
- Target follow-up
- 3 Months
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Benign ovarian tumors | – | Diagnostic Test: ctDNA - circulating tumor DNA, Diagnostic Test: TEP - Tumor Educated PlateletsAll histological proven benign ovarian tumors |
| Malignant ovarian tumors | – | Diagnostic Test: ctDNA - circulating tumor DNA, Diagnostic Test: TEP - Tumor Educated PlateletsAll histological proven malignant ovarian tumors |
| Borderline ovarian tumors | – | Diagnostic Test: ctDNA - circulating tumor DNA, Diagnostic Test: TEP - Tumor Educated PlateletsAll histological proven borderline ovarian tumors |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Women with a suspected malignant ovarian tumor referred to a center for gynecological oncology (CGOA, LUMC or CZE) or one of the four affiliated hospitals (Amphia Ziekenhuis (Breda), HAGA Ziekenhuis (Den Haag), Reinier de Graaf Gasthuis (Delft) of HMC (Den Haag) for surgical treatment.
Key inclusion criteria (6 listed)
- Age ≥18 years
- Presence of a ovarian tumor and referred to specialized center for surgery based on:
- General criteria: a. Understanding of Dutch language b. Fit for surgery (WHO 1-2) c. Written informed consent
Key exclusion criteria (3 listed)
- Suspicion of advanced-stage of disease, e.g. ascites or peritoneal depositions
- History of cancer (excl. BCC) within 5 years prior to inclusion
- Multiple malignancies at the same time
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| ctDNA - circulating tumor DNAlcWGS and WGS of circulating tumor DNA | Diagnostic test | Benign ovarian tumors, Borderline ovarian tumors, Malignant ovarian tumors |
| TEP - Tumor Educated Plateletssequencing miRNA from TEPs | Diagnostic test | Benign ovarian tumors, Borderline ovarian tumors, Malignant ovarian tumors |
Primary outcome
The diagnostic accuracy of the developed algorithm
Time frame: 3 -4 years
The diagnostic accuracy of the developed algorithm, displayed as sensitivity and specificity.
9 secondary outcomes
Cost-effective analysis (I)
Time frame: 3 -4 years
Cost-effective analysis (II)
Time frame: 3 -4 years
Cost-effective analysis (III)
Time frame: 3 -4 years
Psychological Burden (I)
Time frame: 3 -4 years
Psychological Burden (II)
Time frame: 3 -4 years
Psychological Burden (III)
Time frame: 3 -4 years
Psychological Burden (IV)
Time frame: 3 -4 years
Psychological Burden (V)
Time frame: 3 -4 years
Psychological Burden (VI)
Time frame: 3 -4 years
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 21 Jul 2021.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
C.A.R. Lok MD, PhD principal investigator
Dutch Cancer Institute
C.D. de Kroon principal investigator
Leiden University Medical Center / Gynecology
J.M.J. Piek principal investigator
Catharina Ziekenhuis Eindhoven / Gy-necology
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Ovarian Neoplasms, run by The Netherlands Cancer Institute at 4 sites in Netherlands.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 21 Jul 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in Netherlands. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact C.A.R. Lok MD, PhD (00 31 20 512 2975, c.lok@nki.nl), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The diagnostic accuracy of the developed algorithm (time frame: 3 -4 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Jul 2021.