Prediction and Prevention of Venous Thrombo-embolism(VTE) During Chemotherapy Using Serial Determination of Haemostasis Biomarkers.
Conditions: Venous Thromboembolism, Cancer
Sponsor: University of Dublin, Trinity College

 
 
 PROTOCOL 
 
TITLE:   
Prediction of venous thrombosis 
during chemotherapy-the 
PINPOINT study 
Principal Investigator:  
Dr. Lucy Norris (lnorris@tcd.ie) 
 
Co-Investigators 
Professor Feras Abu Saadeh, 
Dr. Dearbhaile Collins, 
Prof. Maeve Lowery 
Dr. Barry Kevane 
Dr. Sharon O’Toole 
Dr. Mark Ward  
Dr. Sinead Cuffe 
Dr. Martin Barr 
Prof Fionnuala Ni Ainle 
Prof. Catherine O’Gorman 
Prof. Karen Cadoo 
Prof John O’Leary 
Dr. Deirdre Kelly 
Prof. Pilib O’Broin 
Dr. David O’Connell 
Dr.  Laura McCullagh 
Dr. Maeve Crowley 
Dr. Oana Deac 
 
Funding 
Health Research Board of Ireland 
 
Funder ref no: 
ILP-POR-2024-029 
 
Sponsor:  
Trinity College Dublin 
(clinicaltrialsponsorship@tcd.ie) 
 
 
Protocol version: 
2.0 
 
Protocol date  
March 2025 
 
 
 

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1.0  
SYNOPSIS 
 
 
Study title:  
PINPOINT: Prediction and prevention of Venous thrombo-embolism(VTE) 
during chemotherapy using serial determination of haemostasis 
biomarkers. 
Objective 
To serially determine plasma levels of haemostatic biomarkers (Thrombin 
generation, Factor VIIIc and Thrombomodulin) and compare their ability to 
predict VTE in cancer patients during chemotherapy compared with the 
Khorana score and the Vienna CAT nomogram. 
Patient Population:  
Inclusion criteria  
• 
Lung, ovarian, gastric, and pancreatic cancers undergoing a new 
course of chemotherapy. 
• 
Aged over 18 
Exclusion criteria 
• 
Prior history of VTE 
• 
History of significant haemorrhage outside of surgical settings 
(previous 5 years) 
• 
Surgery less than 2 weeks prior to first baseline blood sample 
• 
Currently receiving anticoagulant therapy (excluding anti-platelet 
agents) 
• 
Currently on maintenance therapy (or had chemotherapy within 4 
weeks of the first baseline sample) 
 
Number of patients:  
380 
Duration of 
participation:   
6 months 
Primary Endpoint:  
Objectively determined venous thromboembolism during chemotherapy 
 
Study Design: 
• 
Prospective multicentre observational cohort study.  
• 
Blood samples collected at 4 time points:   
➢ Pre chemotherapy (T0) 
➢ 4 weeks post baseline after one cycle of chemotherapy 
(T1) 
➢ 12 weeks post baseline (T2) 
➢ at the end of current line of chemotherapy treatment (4-8 
cycles (months) of chemotherapy) (T3) 
• 
Blood samples: 2 x 3-5 mls in Sodium Citrate tubes 
Study schedule: 
Timepoints 
Consent 
Data 
collection 
Blood 
sampling 
Inclusion  
X 
X 
 
Pre-chemotherapy (T0) 
 
X 
X 
Month 1 (T1) 
 
X 
X 
Month 3 (T2) 
 
X 
X 
End of therapy (T3) 
 
X 
X 
 
 
 
 
 
 
 
 

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2. 
BACKGROUND AND RATIONALE 
2.1 Background 
Venous thromboembolism in cancer and chemotherapy 
The association between malignancy and venous thromboembolism (VTE) is well documented with 
up to 20% of all cancer patients experiencing a VTE during their cancer journey[1]. VTE is a morbid, 
costly and potentially lethal complication of cancer and despite major advances in prophylaxis and 
treatment, VTE is the leading cause of death in cancer patients after the cancer itself[1]. The risk of 
VTE in cancer patients has increased over recent years in tandem with the rising rate of cancer 
worldwide and the increased survival of cancer patients [1].  
Amongst solid tumours, pancreatic, lung, brain, stomach, and ovarian cancer are the most 
prothrombotic and are associated with high rates of VTE depending on tumour histology and 
treatment [2]. Prevention and treatment of cancer associated VTE represents an important medical 
challenge, since oncology patients concomitantly display higher rates of both bleeding and VTE 
recurrence than the non-cancer population [1,2]. This highlights the need for a careful risk/benefit 
assessment of anticoagulant prophylaxis. Recent guidelines recommend that, in ambulatory cancer 
patients receiving systemic therapy, at intermediate/high risk for VTE, thromboprophylaxis with 
Direct Oral Anti-Coagulants (DOACs) should be considered [3,4]. Classification of patients as being at 
low, intermediate, or high risk for VTE should be based on a validated risk assessment tool 
complemented by clinical judgment and experience.  
 
The recommended tool for VTE risk assessment in cancer is the Khorana risk score [5], which was 
designed to identify ambulatory cancer patients at increased risk of VTE during chemotherapy using 
easily available clinical and laboratory variables prior to the commencement of therapy. However, 
the Khorana score performs poorly in cancers of a single type, especially cancers at high risk of VTE 
eg lung and ovary[6]. A validation study of >40,000 patients, showed that the guideline-
recommended Khorana score was not effective in hepatobiliary, pancreatic, lung, or gynaecologic 
cancer[7]. In contrast, a recent report showed that biomarker-driven, risk directed primary 
thromboprophylaxis is effective in gastro-intestinal and lung cancers [8]. 
 
Factor VIIIc, Thrombomodulin(TM), Thrombin generation(TM modified) as biomarkers for VTE 
The biology of chemotherapy associated VTE is complex. Exposure of vascular endothelial cells to 
common chemotherapeutic agents can alter anticoagulant activity with the loss of a 
thromboresistant phenotype[9,10]. Binding of thrombin to thrombomodulin (TM) on the endothelial 
cell surface leads to the activation of protein C(aPC), a major regulatory pathway in coagulation, 
which is accelerated by the endothelial protein C receptor(EPCR)[11]. aPC can inactivate both FVIII 
and FV resulting in a downregulation of thrombin and fibrin production.  Data has shown that the 
aPC pathway is dysregulated during chemotherapy, resulting in a reduction in the inhibitory effects 
of aPC[10]. 
Failure of protein C activation or resistance to the inhibitory effects of aPC(both genetic and 
acquired) is a common cause of VTE in the non cancer population[11]. Factor VIIIc(FVIIIc) has been 
shown to be predictive of VTE in cancer patients with highest levels of FVIIIc in patients who 
developed VTE following chemotherapy compared with matched controls [12,13]. Factor VIIIc is 
predictive of VTE in a variety of clinical settings, even after adjustment for inflammatory markers [23]  
Preliminary studies have shown that plasma levels of soluble TM are reduced in vivo in patients who 
develop VTE following chemotherapy suggesting that TM is an important mediator of chemotherapy 
associated VTE and was inversely correlated with thrombin generation [12]. The thrombin 

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generation assay is associated with increased risk of VTE in cancer patients and sensitivity of the 
assay can be increased by addition of TM. Preliminary data suggests that the TM modified thrombin 
generation assay (TGA-TM) is increased in patients who develop VTE following chemotherapy [12]. 
This data suggests that soluble TM, TGA-TM and FVIIIc levels measured serially may be effective 
alone or in combination as dynamic predictive biomarkers for VTE during chemotherapy. 
 
2.2 Rationale 
Previous studies have used a variety of biomarkers to predict VTE in cancer patients, however 
prediction was based on one sample and does not account for the dynamic nature of 
thrombogenesis particularly during chemotherapy, when the progressive effects of endothelial 
damage, material from dying tumour cells and an inflammatory response may combine to produce 
VTE[12].  The interplay between cancer, coagulation activation and chemotherapy is a dynamic 
process, unlikely to be represented by a single risk assessment at the start of therapy. Dynamic risk 
assessment using serial measurement of biomarkers during therapy has been recommended as a 
more effective approach to risk assessment [14,4]. The most recent ESMO guidelines have suggested 
repeated risk assessment using the new Vienna CAT score (a nomogram based on D-dimer levels and 
tumour site) may improve risk prediction [4] however this has not been tested and the specificity of 
D-dimer as a biomarker for VTE in this setting is low [15].  Recent validation studies of a single 
measurement of the Vienna- CAT nomogram showed only a modest improvement in discriminatory 
ability compared with the Khorana score [16]. VTE risk is exacerbated by chemotherapy and hence 
biomarkers which capture the effects of chemotherapy on thrombus formation are more likely to be 
reflective of chemotherapy associated VTE.  
 
2.3 Hypothesis 
Serial determinations of TGA-TM, FVIIIc and TM will predict VTE in ovarian, pancreatic, lung and 
gastric cancer patients undergoing chemotherapy more effectively that the guideline recommended 
Khorana score or serial determinations of the Vienna CATS score. 
 
2.4 Planned analysis 
Lung, ovarian, gastric and pancreatic cancer patients (n=380) who are scheduled to undergo 
chemotherapy will be recruited from three large centres for cancer treatment in Ireland (Trinity St. 
James Cancer Institute, Cork University Hospital, Mater Hospital). The primary endpoint for the study 
will be objectively diagnosed VTE which occurs during chemotherapy. Following full and informed 
written consent, venous blood samples will be obtained pre-treatment, after month 1, 3 and at the 
end of treatment (or prior to interval cytoreductive surgery in the case of neoadjuvant patients). 
Plasma levels of TGA-TM, sTM, FVIIIc and D-dimer will be measured at each time point. All biomarker 
analysis will take place in the Coagulation Research Laboratory, Dept of Gynaecology, Trinity St. 
James Cancer Institute. The Khorana score will be calculated at the start of therapy in each patient. 
The Vienna CAT score will be calculated at each time point using the D-dimer values obtained. Serial 
levels of each biomarker in patients who develop VTE will be compared with those who remain 
thrombosis free. The predictive ability of each biomarker (alone and in combination) will be 
compared with (1) the current recommended risk assessment model (Khorana score) performed 
prior to treatment and (2) serial determinations of the Vienna CAT nomogram at each timepoint.  
 
3.0 
OBJECTIVE OF THE STUDY 
 
The aim of the study is to serially measure TGA-TM, sTM, and FVIIIc levels in lung, ovarian, 
pancreatic, and gastric cancer patients during chemotherapy and compare their ability to predict 
VTE with the Khorana score and serial determinations of the new Vienna CAT score. 
 
4.0  
STUDY ENDPOINT 
 

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Objectively diagnosed VTE occurring during chemotherapy 
 
5.0  
PATIENT POPULATION 
 
All patients with a diagnosis of ovarian, lung, gastric or pancreatic cancer who are scheduled to 
undergo a course of chemotherapy are eligible for the study. 
 
5.1 
Patient Selection Criteria 
 
5.1.1 
Inclusion criteria 
 
• 
Patients with a diagnosis of ovarian, lung, gastric or pancreatic cancer who are scheduled to 
undergo a course of chemotherapy who: 
 
 
are undergoing adjuvant or neoadjuvant chemotherapy 
 
or 
 
who are undergoing chemotherapy for relapsed disease 
 
or  
 
Patients who are undergoing targeted therapy in combination with chemotherapy 
 
• 
Patients who are over 18 years of age  
• 
Patients who are able to give full and informed written consent 
 
 
5.1.2 
Exclusion criteria 
 
• 
Prior history of a documented VTE event within the last 5 years (excluding central line 
associated events whereby patients completed anticoagulation > 3 months previously) 
• 
Any history of significant haemorrhage (requiring hospitalization or transfusion) outside of a 
surgical setting within the last 5 years 
• 
Familial bleeding diathesis 
• 
Known diagnosis of disseminated intravascular coagulation 
• 
Surgery within 2 weeks of first baseline sample (with the exception of porth-a-cath 
implantation or biopsy) 
• 
Chemotherapy or immunotherapy 4 weeks before first baseline sample 
• 
Currently receiving long term anticoagulant therapy (Low Molecular Weight Heparin(LMWH), 
Direct Oral Anticoagulants(DOACs), Warfarin). Patients receiving aspirin, ticlopidine, 
clopidogrel or LMWH at a thrombo-prophylactic dosage for a short period (ie post cancer 
surgery or during short hospital stay) will be included provided they have completed 
thromboprophylaxis therapy at the first blood sampling time point. 
 
5.2 
Recruitment and consent 
Eligible patients receiving treatment at each of the study centres (St. James Hospital, Mater Hospital 
and Cork University hospital) will be invited to participate by a member of the investigator team.  
Patients will be provided with the study information (patient information leaflet and consent form) 
and will give full written consent in person if participating in the study.   
 
5.3 
Number of patients 
 
The accrual target is 380 patients. 
 

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5.4 
Anticipated enrolment period and study completion date 
 
The anticipated enrolment period is 36 months.  The study enrolment will be completed in 2028. The 
final sample and data collection will be June 2029 
 
5.5 
Duration of patient participation 
 
Patients will participate from the date of enrolment until completion of the current line of treatment 
(4-6 cycles of chemotherapy), occurrence of a VTE, or 6 months from enrolment as appropriate.   
 
 
5.6  
Patient and study discontinuation criteria 
 
Patients are free to withdraw from the study at any time upon request.   
 
Additional reasons for withdrawal 
 
• 
Study completion 
• 
Long term anticoagulation (prophylaxis or treatment) 
• 
Lost to follow-up 
• 
Discontinuation of chemotherapy 
• 
Death 
• 
Other 
• 
Investigator decision 
 
 
6.  
STUDY DESIGN 
 
6.1  
Type of study design 
Multicentre prospective observational cohort study 
 
6.2 
Timing of sample and data collection 
 
6.2.1. Blood Sample collection 
Venous blood samples (1 x 5ml Na Citrate) will be taken into 3.13% sodium citrate (1:9) tubes with 
the minimum venous stasis at the time of routine pre-chemotherapy blood draws.  Blood samples 
will be taken before the first cycle(T0), second cycle (T1), after the third cycle (T2) of chemotherapy.  
The final sample will be following 4-6 cycles of chemotherapy or at the end of the current line of 
treatment (T3).  All samples will be taken to coincide with the patient’s routine blood samples. For 
patients on weekly chemotherapy, T1 will be taken after 3-4 weeks, T2 at 10-12 weeks, T3 at the end 
of current weekly treatment. 
 
Timepoints 
Consent 
Data 
collection 
Blood sampling 
Inclusion  
X 
X 
 
Pre-chemotherapy (T0) 
 
X 
X 
Month 1 (T1) 
 
X 
X 
Month 3 (T2) 
 
X 
X 
End of therapy (T3) 
 
X 
X 
 

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6.2.2 
 Sample processing  
Samples will be centrifuged at 2000 g for 20 minutes at 4°c in the processing laboratory in each 
centre. The resulting platelet poor plasma will be carefully removed and aliquoted into 5 x 500µl 
aliquots in labelled microtubes. All tubes will be labelled with the patient study number and the 
date.  Aliquots will be snap frozen and stored at -80°c.  All samples should be processed and stored 
within 2 hours of phlebotomy.  Samples will be stored at each centre and transferred in batches to 
the Coagulation Research Laboratory, Dept of Obstetrics and Gynaecology. Trinity St. James Cancer 
Institute for analysis.  All sample transport costs will be covered by the Coagulation Research 
laboratory. 
 
6.2.3 
Data collection 
The study data will be collected using REDCAP( https://www.project-redcap.org/ ). Study data will be 
entered by authorised site personnel into the electronic data capture system. 
 
 
The following data will be collected for each patient. 
 
Inclusion/baseline (T0) 
 
• 
Age 
• 
Weight 
• 
Sex 
• 
BMI  
• 
Consent yes/no 
• 
Inclusion/exclusion criteria 
• 
Date of diagnosis 
• 
Tumour site 
• 
Tumour histology 
• 
Stage of cancer 
• 
Grade of cancer 
• 
Relevant past Medical history (Diabetes Mellitus, Hypertension,Chronic liver or kidney 
disease,  Chronic respiratory disease, heart disease, cancer, auto-immune disease, 
neurological disease)  
• 
ECOG status 
• 
 Relevant current medication- Aspirin, Clopidogrel, Dipyridamole, Ticagrelor, Ticlopidine. 
• 
Date of surgery (if applicable) 
• 
Previous chemotherapy  
• 
Haemoglobin (on day of T0 blood sampling) 
• 
White cell count 
• 
Neutrophils 
• 
Lymphocytes 
• 
Platelets 
 
 
Follow up blood sampling visits.   T1-T3 
 
• 
Chemotherapy treatment details 
• 
Number of cycles completed 
• 
New/discontinued relevant medication  
• 
New diagnosis of relevant conditions (see list at baseline visit) since last visit-  

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• 
VTE since baseline:  Yes/No 
If yes: 
o Date of VTE diagnosis (date of CTPA, VUS as appropriate) 
o VTE details- PE. DVT etc 
 
• 
Hospital admissions since last visit 
o Date of admission 
o Duration of hospital stay 
o Reason for admission 
o VTE prophylaxis during admission  
 
• 
Laboratory values (most recent result) 
o Haemoglobin 
o White cell count 
o Neutrophils 
o Lymphocytes 
o Platelets 
 
 
6.3 
Laboratory Biomarker analysis:   
 
All biomarker analysis will take place at the Coagulation Research Laboratory, Dept of Obstetrics and 
Gynaecology, Trinity St. James Cancer Institute, St. James’s Hospital.   
 
6.3.1  Laboratory methods 
sTM will be measured using Enzyme Linked Immunosorbent Assay (ELISA) (R&D systems) and FVIIIc 
will be measured using commercially available chromogenic substrate assay (Hyphen Biomed 
France). TGA-TM will be measured using commercially available reagents (Stago) as previously 
described [10]. D-dimer will be measured using a 2-step procedure (VidasTM D-dimer Exclusion II, 
Biomerieux, France). 
 
6.3.2 
Calculation of the Khorana risk score(KRS) and the Vienna CAT score 
BMI data and complete blood cell count values will be recorded at enrolment prior to the start of 
chemotherapy. and the KRS calculated as previously described [5]. Lung and ovarian cancer patients 
are assigned 1 point for tumour site category, gastric and pancreatic cancers are assigned 2 points. 
The Vienna CAT nomogram will be calculated according to the published formula [17] at each 
sampling point in the study. Calculation of the Vienna CAT score and the KRS will be performed by 
the biomarker laboratory from the collected data. 
 
 
7.0 
STATISTICAL CONSIDERATIONS  
7.1 Analysis  
Statistical analysis of the primary outcome data will be performed by Dr. Lucy Norris in collaboration 
with Prof. Pilib O’Broin, School of Mathematical & Statistical Sciences, University of Galway.  
7.2  Sample size calculation 
Power calculations will be based on previous data [12]. sTM FVIIIc, TGA-TM effect sizes and standard 
deviations of the outcome variable were 92.1(154), 1050 (1441), 34 (45.96) respectively. Type I error 
is set at 0.01 to allow for the effect of multiple time points and type II.error = 0.2. A minimum of 31 
patients in the VTE group will be required. Given a predicted incidence of VTE of 10-20%, this 

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requires a sample size of 310 patients to complete the study at a 10% VTE incidence rate.  Allowing 
for dropouts, 380 patients will be recruited to the study. Sample sizes for regression analysis are 
estimated using a rule of thumb of 10 individuals expected to experience the event (VTE) for each 
predictor in the model. In this instance, with an expected 10-20% incidence of VTE, if 30-60 
individuals experience VTE, this will allow 3-6 predictors to be fitted to the model.  
 
 
 
7.2 Statistical analysis of the data 
Analysis will be performed when the required data has been received following completion of 
patient enrolment and all biomarker analysis is complete. Data will be assessed for normal 
distribution and log transformed where normal distribution criteria are not met. Biomarker data will 
be reported as continuous data and will be reported as median (25-75th centile). Potential 
confounders will first be identified using univariate analysis of clinical risk factors to identify 
differences between VTE cases and controls.  These covariates will then be incorporated into the 
model.  
The JMBayes2 R package from the Rizopoulos group (https://drizopoulos.github.io/JMbayes2/) will 
be used to fit a joint model using a Markov chain Monte Carlo (MCMC) approach. The first sub-
model, a multivariable linear mixed model will be used to model longitudinal changes in the three 
biomarkers; the second sub-model, a competing risks model, will be used to model the time-to-event 
data. Using this approach, the first sub-model will account for the non-independence of repeated 
measures from the same patient while allowing for missing longitudinal data, while the second sub-
model will also allow for the inclusion of clinically relevant covariates such as treatment type, tumour 
site etc.  The resulting associations will be compared with current models (Vienna CATS score) to 
identify which biomarker or biomarker(s)have the strongest association with VTE.  Sensitivity, 
specificity, NPV, PPV of the biomarker(s) above/below a cutoff will also be compared with the 
Khorana score and the Vienna CATS score.  Statistical analysis of pseudonymised data will take place 
in the Dept of Mathematics, University of Galway (Prof Pilib O’Broin). 
 
8.0 
ADMINISTRATIVE RESPONSIBILITIES 
  
8.1 Good Clinical Practice  
The study will be conducted in accordance with the International Conference on Harmonisation (ICH) 
Good Clinical Practice (GCP). The investigator will be thoroughly familiar with the study 
requirements as outlined in the protocol. Essential clinical documents will be maintained to 
demonstrate the validity of the study and the integrity of the data collected. Master files should be 
established at the beginning of the study, maintained for the duration of the study and retained 
according to the appropriate regulations.  
 
8.2 Ethical considerations  
The study will be conducted in accordance with ethical principles founded in the Declaration of 
Helsinki (current edition located at: http://www.wma.net/en/30publications/10policies/b3/).  
An ethics committee at each centre will review all appropriate study documentation in order to 
safeguard the rights, safety and well-being of the patients. The protocol, informed consent, written 
information given to the patients, annual progress reports and any revisions to these documents will 
be provided to them by the sponsor. The study will only be conducted at sites where their full 
approval has been obtained.  Explicit consent will be obtained through the consent form. 
Participation or non-participation in the study will not affect the patient’s medical treatment in 
the hospital. 

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8.3 Data Protection 
A data protection impact assessment (DPIA) will be conducted and reviewed by the Trinity 
College Data Protection Officer (DPO) and the DPO in each participating hospital.  
 
Published guidelines to be followed:  
• 
Human Rights Privacy and Confidentiality  
• 
TCD Good Research Practice Policy  
 
Data Protection Legislation  such as the Data Protection Acts 1988 to-2018 will be complied 
with. 
 
The legal basis for processing personal data in the study is under Article 6(1)(e) and Article 
9(2)(j)  - research in the public interest. Explicit consent will also be given as a safeguard under 
the Health Research Regulations  2018 ( As amended) 
 
Pseudonymised study data will be held securely on site in the Trinity St. James Cancer Institute, 
St James’s Hospital.  Patient consent forms will be retained for 7 years on site at each centre. 
 
 

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