Thrombosis is the second-most common cause of death in cancer patients after the cancer
itself and is a significant contributor to morbidity and decreased quality of life
in these patients.[1]
[2]
[3] Both arterial thrombosis and venous thromboembolism (VTE) occur in cancer, and while
arterial thrombosis, especially ischemic stroke,[4] in cancer has gained focus in recent years, VTE is still the most prevalent type
of thrombosis in cancer. The present review focuses on the prediction of VTE in patients
with cancer and does not cover arterial thrombosis.
VTE can be effectively prevented with thromboprophylactic drugs. However, these drugs
potentiate the increased risk of bleeding already present in cancer patients.[5]
[6] It is therefore important to correctly identify and select cancer patients who can
benefit from thromboprophylaxis and avoid treating those where treatment is unnecessary
or even harmful. To this end, several risk assessment models have been developed to
help clinicians identify cancer patients at increased risk of VTE.[7]
[8]
[9]
[10]
[11]
The Khorana score forms the basis of most of the scores. It was developed in 2008
and designed for the prediction of VTE in cancer patients receiving chemotherapy.[7] Several later scores have expanded or amended the Khorana scores, such as the Vienna
Cancer and Thrombosis (CATS) score,[8] the PROTECHT score,[9] and the ONKOTEV score.[10] Other scores have been developed independently of the Khorana score, aiming to reduce
the complexity of the scoring and increase clinical applicability.[11]
[12] The risk assessment models have been validated in several subsequent studies.[13]
[14]
[15] Here, the results have been mixed, and the clinical applicability of the scores
has varied.[13]
[15] All the risk scores rely on a combination of clinical data and biochemical parameters.
An important aspect of the work to improve these scores is the investigation of additional
potential biomarkers of VTE.
A promising category of biomarkers is analyses measuring thrombin activity. Thrombin
is the product of the coagulation cascade, responsible for converting fibrinogen to
fibrin and forming a stable clot. Apart from its role in clot formation, thrombin
also inhibits fibrinolysis through thrombin activatable fibrinolysis inhibitor and
activates platelets through their thrombin receptor.[16] It is well established that cancer patients have increased thrombin formation, driven
by an increase in tissue factor expression on endothelium and circulating tumor-derived
microparticles and through interactions with the endothelium, immune cells, and platelets.[16]
[17] Anticancer therapies may further enhance thrombin formation ([Fig. 1]). Interestingly, thrombin also seems to promote cancer growth and development by
interactions with the endothelium and the tumor cells.[16]
[17]
[18] As such, thrombin is an integral player in the development of thrombosis in cancer
and might be a promising biomarker for VTE prediction. However, due to the short half-life
of thrombin in blood, it is not possible to directly quantify the amount of circulatory
thrombin at any given time.[16] Therefore, it is necessary to measure more stable by-products of thrombin (e.g.,
prothrombin fragment 1.2 (F1.2) and thrombin-antithrombin complex (TAT), or ex vivo
thrombin generation potential). F1.2 is the by-product when thrombin is cleaved from
prothrombin and is generated in a 1:1 ratio to thrombin.[19] TAT formation takes place when active thrombin is bound by antithrombin. TAT increases
when there is an overflow of free thrombin and is therefore increased in the prothrombotic
state.[16]
[20] Both thus reflect in vivo thrombin formation, and both have considerably longer
half-life than thrombin and are therefore better suited as biomarkers.
Fig. 1 Thrombin generation in cancer. The figure shows a simplified outline of some of the
mechanisms behind increased thrombin generation in cancer. Cancer cells may directly
express tissue factor as well as release negatively charged EVs whose surface promote
coagulation. Cancer cells also increase inflammation in the form of proinflammatory
cytokines that further thrombin generation. Lastly, cancer cells increase platelet
and vascular endothelium activation, which also leads to thrombin generation. Surgery
induces tissue damage that also furthers coagulation, and chemotherapy increases TF
activity, activates platelets, and induces procoagulant apoptotic cell debris.[17]
[18] EVs, extracellular vesicle(s); TF, tissue factor; VWF, von Willebrand Factor. Figure
created with BioRender.
Thrombin generation can also be measured ex vivo by the addition of activators (calcium,
phospholipids, and tissue factor) and a thrombin-specific, fluorogenic substrate to
platelet-poor or -rich plasma. The resulting thrombin generation curve is conventionally
described with the parameters lagtime, time to peak, peak thrombin concentration,
and endogenous thrombin potential (ETP).[21]
[22] Furthermore, the mean rate index may be calculated as peak thrombin concentration/(time
to peak – lagtime).
F1.2, TAT, and ex vivo thrombin generation are all expressions of thrombin activity.
However, their applicability as VTE biomarkers in a clinical setting is not sufficiently
understood. We therefore aimed to systematically review the existing evidence in the
literature to examine if these three selected markers of thrombin generation can predict
VTE in cancer patients.
Materials and Methods
The present review follows the Preferred Reporting Items for Systematic Reviews and
Meta-Analysis guidelines.[23] The search was performed in the PubMed and Embase databases in July 2023. Search
strings were composed of indexed terms and freeform terms for cancer, thrombosis and
F1.2 and/or TAT and/or thrombin generation. The full search strings are presented
in [Table 1].
Table 1
Search strings in PubMed and Embase
|
PubMed
|
(“Neoplasms”[MeSH Terms] OR cancer* OR neoplasm* OR malignanc*) AND (“Embolism and
Thrombosis”[MeSH Terms] OR “venous thromboembolism” OR “venous thrombo-embolism” OR
“venous thrombosis” OR “deep vein thromboembolism” OR “deep vein thrombosis” OR “portal
thrombosis” OR “sinus thrombosis” OR “mesenterial thrombosis” OR “cerebral vein thrombosis”
OR “cancer-associated thrombosis” OR “VTE” OR “DVT”) AND (“Thrombin”[MeSH] OR “thrombin”
OR “calibrated automated thrombogram” OR “thrombography” OR “prothrombin fragment
1.2” [Supplementary Concept] OR “prothrombin” OR “antithrombin III-protease complex”
[Supplementary Concept] OR “TAT” OR “thrombin-antithrombin”)
|
|
Embase
|
('malignant neoplasm'/exp OR cancer* OR neoplasm* OR malignanc*) AND ('thromboembolism'/exp
OR “venous thromboembolism” OR “venous thrombo-embolism” OR “venous thrombosis” OR
“deep vein thromboembolism” OR “deep vein thrombosis” OR “portal thrombosis” OR “sinus
thrombosis” OR “mesenterial thrombosis” OR “cerebral vein thrombosis” OR “cancer-associated
thrombosis” OR “VTE” OR “DVT”) AND ('thrombin'/exp OR 'thrombography'/exp OR “thrombin”
OR “calibrated automated thrombogram” OR “thrombography” OR “prothrombin” OR 'thrombin
antithrombin complex'/exp OR “TAT” OR “thrombin-antithrombin”) NOT 'conference abstract'/it
|
Inclusion Criteria
We included studies on patients with both solid and hematologic cancers that recorded
VTE and included measurements on F1.2, TAT, and/or ex vivo thrombin generation. VTE
was defined as either (1) distal or proximal deep venous thrombosis in upper or lower
extremity, (2) pulmonary embolism, (3) cerebral venous sinus thrombosis, or (4) splanchnic,
portal, or other thromboses in veins in or supplying organs and which had been confirmed
with relevant imaging techniques. Prospective cohort, case-control, cross-sectional,
post-hoc, and randomized controlled studies in English were accepted.
Exclusion Criteria
Exclusion criteria were conference abstracts, studies with a nonpredictive design
(diagnosis of VTE prior to measurement of thrombin generation parameters), studies
that did not report their thrombin generation results in numbers or graphically, studies
that did not perform statistical analysis of the association between thrombin generation
parameters and VTE, studies with no original data, case reports with <10 cases, and
studies that had no VTE events.
Data Extraction
After duplicate sorting and exclusion, 50 abstracts were screened by two authors (T.G.
and J.B.L.) to validate the inclusion and exclusion criteria. The remaining abstracts
were subsequently screened by either author (T.G. or J.B.L.). If eligibility could
not be determined from the abstract, the study record was included for full-text screening.
After abstract screening, 10 study records were randomly selected for full-text reading
by both T.G. and J.B.L. to revalidate the inclusion and exclusion criteria. The remaining
study records were read in full text by T.G. or J.B.L. and either included or excluded
according to the predefined criteria.
Quality Assessment
Quality assessment of the included studies was performed by the authors T.G. and J.B.L.
using the applicable study quality assessment tool from the National Heart, Lung,
and Blood Institute.[24]
Data Synthesis
According to the protocol, more than five studies had to report a mean value for the
selected biomarker in both the VTE and non-VTE groups, in order to conduct a meta-analysis.
Two studies reported a mean F1.2, four reported a TAT mean, and only one study reported
a mean thrombin generation. Thus, a qualitative synthesis of the included studies
was performed.
Results
From a total of 4,510 papers identified in the literature search, 24 papers were included
in the final review ([Fig. 2]). Of these, 11 studies reported data on F1.2[15]
[19]
[25]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
[33] ([Table 2]), nine studies reported data on TAT[25]
[26]
[27]
[30]
[33]
[34]
[35]
[36]
[37] ([Table 3]), and 12 studies reported data on thrombin generation[13]
[21]
[28]
[29]
[31]
[38]
[39]
[40]
[41]
[42]
[43]
[44] ([Table 4]). Of the 24 included papers, 13 were rated as good, eight as fair, and three studies
were rated as poor.
Table 2
Studies measuring prothrombin factor 1.2 (F1.2)
|
Author, year, quality assessment
|
Study design
|
Population
|
Thromboprophylaxis
|
Assay,
sample timing
|
Outcomes, VTE definition and incidence
|
Findings
|
|
Ay et al
2009[19]
Good
|
Prospective observational[a]
|
Mixed cancer patients (n = 821).
Age: 62 y (53-68)
Female: 45%
Site of cancer: Brain (12%), breast (16%), lung (15%), stomach (4%), colorectal (13%),
pancreas (6%), kidney (3%), prostate (12%), multiple myeloma (2%), lymphoma (11%)
and other (6%)
|
Excluded If therapeutic.
Short-term heparin prophylaxis allowed but NR
|
Enzygnost F1 + 2
At inclusion
|
Incident symptomatic VTE confirmed with imaging or autopsy
VTE incidence: 8% (n = 62) in median 501 d FU
PE (47%), lower extremity DVT (44%) and other (10%)
|
F1.2 ↑ in VTE vs. non-VTE:
310 (213–416) vs. 249 (190–353) pmol/L, p = 0.003
With 75% cut-off: 358 pmol/L
Univariate analysis:
HR = 2.2 (CI: 1.3–3.6), p < 0.003
Multivariate, adjusted analysis:
HR = 2.0 (CI: 1.2–3.6), p = 0.02
|
|
Falanga et al
1993[25]
Fair
|
Prospective observational
|
Solid cancer patients undergoing surgery (n = 117)
Age range: 40–62 y (median NR)
Female: 36%
Site of cancer: Gastrointestinal (80%), lung, breast, kidney, or thyroid (20%)
|
Heparin prophylaxis for 7 d (n = 83)
No prophylaxis (n = 34)
|
Enzygnost F1 + 2
Before surgery.
|
Screening for incident VTE with 125I-fibrinogen uptake test after surgery, confirmed with imaging
VTE incidence: 8% (n = 9) in 7 d FU
All lower extremity DVT
|
F1.2 ↔ in VTE vs. non-VTE:
Relative risk of VTE with cut-of ≥ 1.1 nM:
RR = 1.75 (CI: 0.46–6.61), p NS, value NR
|
|
Iversen et al
1996[26]
Good
|
Prospective observational[b]
|
Colorectal cancer patients undergoing surgery (n = 93).
Age: 72 y (41–91)
Female: 47%
|
Heparin prophylaxis for at least 7 d
|
Enzygnost F1 + 2
Before surgery
|
Screening for incident VTE with imaging after surgery
VTE incidence: 22% in 12 d FU (n = 20)
PE (5%), DVT (95%)
|
F1.2 ↔ in VTE vs. non-VTE:
1.8 nM (1.7–2.4) vs. 1.8 (1.6–2–0), p NS, value NR
|
|
Iversen et al
2002[27]
Good
|
Prospective observational[b]
|
Colorectal cancer patients undergoing surgery (n = 137)
Age: 75 y, range 41–84
Female: 50%
|
Heparin prophylaxis for at least 7 d
|
Enzygnost F1 + 2
Before surgery and postoperative day 1, 2, and 7
|
Screening for incident VTE with imaging after surgery in 93% of patients (n = 128)
VTE incidence: 20% (n = 26) in 12 d FU
PE + DVT (4%), DVT (96%)
|
F1.2 ↑ VTE vs. non-VTE[c]:
Before surgery: Geometric mean 2.01 nmol/L (CI: 1.72–2.36) vs. 1.75 nmol/L (1.62–1.90),
p NR
Postoperative day 1: 3.80 vs. 2.15 nmol/L, p < 0.002
Postoperative day 2: 2.75 vs. 2.25 nmol/L, p < 0.01
Postoperative day 7: 3.75 vs. 3.35 nmol/L, p NR
|
|
Pépin et al
2016[15]
Good
|
Case-control (derived from prospective observational cohort)
|
Ambulatory solid cancer patients receiving chemotherapy (n = 160, consisting of 20 cases with VTE and 140 controls without)
Mean age: 61 ± 9.9 y
Female: 40%
Site of cancer: Pancreas (40%), gastrointestinal (40%), lung (15%), other (5%)
|
Patients in therapeutic doses excluded. Prophylaxis NR.
|
Enzygnost F1 + 2
At inclusion
|
Screening for incident VTE with imaging at inclusion. Further scanning if clinical
suspicion
VTE incidence in prospective cohort: 5% in 6 mo FU (n = 23 of 443)
Type NR.
|
F1.2 ↔ VTE vs. non-VTE:
Mean 439 ± 223 vs. 425 ± 781 pmol/L, p NS, value NR
|
|
Posch et al
2016[28]
Good
|
Prospective observational[a]
|
Newly diagnosed or remitting cancer patients (n = 804)
Age: 63 y (54–69)
Female: 54%
Site of cancer: Brain (11%), breast (17%), gastrointestinal (18%), kidney (3%), lung
(15%), lymphoma (11%), other (8%), pancreas (7%), prostate (12%)
|
Anticoagulants not allowed
|
Enzygnost F1 + 2
At inclusion
|
Incident VTE detected by routine imaging or due to clinical suspicion
VTE incidence: 7% (n = 55) in 2 y FU
Type NR
|
F1.2 ↑ in VTE vs. non-VTE:
Univariate risk score for VTE with 1 SD increase in F1 + 2: Subdistribution HR = 1.48
(CI: 1.23–1.78), p < 0.001
|
|
Reitter et al
2016[29]
Good
|
Prospective observational[a]
|
Solid cancer patients beginning chemo- or radiotherapy (n = 112)
Age: 62 y, range 21–80
Female: 43%
Site of cancer: Brain (35%), colorectal (13%), lung (37%) and pancreas (15%)
|
Short-term heparin prophylaxis allowed but NR
|
Enzygnost F1 + 2
At inclusion
|
Symptomatic incident VTE confirmed by imaging or autopsy report
VTE incidence: 13% (n = 14) in 250 d FU
PE (29%), DVT (50%) and other
|
F1.2 ↑ in VTE vs. non-VTE:
Per twofold increase in F1 + 2 HR = 2.11 (CI: 1.47–3.03), p < 0.0001
|
|
Sallah et al
2004[30]
Good
|
Prospective observational
|
Solid cancer patients with diagnosis of first VTE (n = 223)
Age: 57 y (IQR NR)
Female: 50%
Site of cancer: Breast (20%), colorectal (16%), genitourinary (17%), head and neck
(14%), lung (18%), and other (15%)
|
All patients on vitamin K antagonists for at least 6 mo
|
Enzygnost F1 + 2
Before initiation of anticoagulation
|
VTE recurrence confirmed by imaging
Incidence of recurrent VTE: 14% (n = 31)
Type NR
|
F1.2 ↔ in VTE vs. non-VTE:
Full cohort:
Median 3.7 and mean 4.3 nmol/L
VTE recurrence group: Median 4.4 and mean 5.1 nmol/L, p and IQR/range NR
Univariate regression for VTE recurrence (cut-off NR): OR = 1.30 (CI: 0.97–1.73),
p = 0.07
|
|
Thaler et al
2014[31]
Good
|
Prospective observational[a]
|
Newly diagnosed high-grade glioma patients, 2–3 wk after surgery (n = 141)
Age: 54 y (44–64)
Female: 33%
|
Patients in therapeutic doses excluded. Prophylaxis 8–10 d postsurgery
|
Enzygnost F1 + 2
Sampling at inclusion
|
Symptomatic incident VTE confirmed by imaging or autopsy report
VTE incidence: 17% in 2 y FU (n = 24)
PE (46%), DVT (54%)
|
F1.2 ↔ VTE vs. whole cohort:
286 pmol/L (167–435) vs.
224 pmol/L (156–324), p NR
Univariate HR for prediction of VTE per doubling of F1.2: 1.59 (CI: 1.02–2.41), p = 0.041
Multivariate HR = 1.53 (0.97–2.36), p = 0.069
|
|
Tsubata et al
2022[32]
Poor
|
Prospective observational
|
Nontreatable lung cancer (newly diagnosed or remission) (n = 1,008)
Age: 70 y, range 30–94
Female: 29%
|
NR. Some patients receiving Edoxaban treatment included in this cohort
|
Assay NR
Timing NR
|
All patients screened with CT and ultrasound at inclusion. Symptomatic incident and
recurrent VTE were recorded during the FU period.
VTE incidence: 4% in 2 y FU (n = 38)
Type NR
|
F1.2 ↑ in VTE vs. non-VTE:
Univariate analysis of VTE risk with cut-off F1 + 2 ≥ 325 pmol/L
OR = 1.120 (CI: 1.073–1.169), p = 0.000
Risk assessment model for the development of VTE: Coefficient = 0.768, OR = 2.155
(CI: 1.313–3.535), p = 0.002
|
|
van Doormaal et al
2012[33]
Fair
|
Prospective observational
|
Mixed cancer patients (n = 43)
Age: 59 ± 12 y
Female: 42%
Site of cancer: Breast (19%), gastrointestinal (37%), pancreatic (30%) and other (14%)
|
No anticoagulant use allowed at inclusion
|
Enzygnost F1 + 2
Sampling at inclusion
|
Symptomatic incident VTE confirmed with imaging and recorded during the FU period
VTE-incidence: 11.6% (n = 5) in 6 mo FU
PE (40%), DVT (40%) and other (20%)
|
F1.2 ↔ VTE vs. non-VTE group:
319 (187–558) vs. 241
(179–312) pmol/L, p = 0.427
|
Abbreviations in table: AUC, area under the curve, CI, 95% confidence interval, CT,
computed tomography, DVT, deep venous thrombosis, ELISA, enzyme-linked immunosorbent
assay, F1 + 2, prothrombin fragment 1 + 2, FU, follow-up, HR, hazard ratio, IQR, interquartile
range, LMWH, low molecular weight heparin, MRI, magnetic resonance imaging, NR, not
reported, NS, nonsignificant, OR, odds ratio, ROC, receiver operating characteristic,
RR, relative risk, SD, standard deviation, SE, standard error, TF, tissue factor,
VTE, venous thromboembolic event(s).
Note: Age and findings reported as median (IQR) unless stated otherwise.
Note: ↔ no change, ↑ increased.
a Study population part of the same cohort (the Vienna CATS-study).
b Study population part of the same cohort.
c Findings on postoperative day 1, 2 and 7 were read from Figure 3 in publication.
Table 3
Studies measuring thrombin-antithrombin complex (TAT)
|
Author, year, quality assessment
|
Study design
|
Population
|
Thromboprophylaxis
|
Assay, sample timing
|
Outcomes, VTE definition and incidence
|
Findings
|
|
Falanga et al
1993[25]
Fair
|
Prospective observational
|
Solid cancer patients undergoing surgery (n = 117).
Age range: 40–62 y (median NR)
Female: 36%
Site of cancer: Gastrointestinal (80%), lung, breast, kidney or thyroid (20%)
|
Heparin prophylaxis for 7 d (n = 83)
No prophylaxis (n = 34)
|
Enzygnost TAT
Before surgery
|
Screening for incident VTE with 125I-fibrinogen uptake test after surgery, confirmed with imaging
VTE incidence: 8% (n = 9) in 7 d FU
All lower extremity DVT
|
TAT ↑ in VTE vs. non-VTE:
Risk of with VTE with cut-off > 3.5 ng/mL:
RR = 7.5 (CI: 1.65–34.6), p < 0.01.
Sensitivity 78%, specificity 72%, positive predictive value 23% and negative predictive
value 97%.
|
|
Iversen et al
1996[26]
Good
|
Prospective observationalb
|
Colorectal cancer patients undergoing surgery (n = 93)
Age: 72 y (41–91)
Female: 47%
|
Heparin prophylaxis for at least 7 d
|
Enzygnost TAT
Before surgery
|
Screening for incident VTE with imaging after surgery
VTE incidence: 22% (n = 20)
PE (5%), DVT (95%).
|
TAT ↔ in VTE vs. non-VTE:
3.5 (CI: 3.0–6.0) vs. 3.0 µg/L (3.0–4.0), p NS, value NR
|
|
Iversen and Thorlacius-Ussing
2002[27]
Good
|
Prospective observationalb
|
Colorectal cancer patients undergoing surgery (n = 137)
Age: 75 y, range 41–84
Female: 50%
|
Heparin prophylaxis for at least 7 d
|
Enzygnost TAT
Before surgery
|
Screening for incident VTE with imaging after surgery in 93% of patients (n = 128)
VTE incidence: 20% (n = 26) in 12 d FU
PE + DVT (4%), DVT (96%)
|
TAT ↑ VTE vs. non-VTE[c]:
Before surgery: Geometric mean: 3.83 (CI: 3.07–4.78) vs. 3.72 μg/L (3.30–4.19), p
NR
Postoperative day 1: 15 vs. 12 μg/L, p < 0.03
Postoperative day 2: 11 vs. 9.5 μg/L, p NR
Postoperative day 7: 9 vs. 7 μg/L, p NR
|
|
Kirwan et al
2008[34]
Poor
|
Prospective observational
|
Breast cancer patients commencing chemotherapy as an incidence (postsurgery) treatment
or as treatment for metastatic disease (n = 123)
Age: 52 y, range 31–78
Female: 100%
|
No anticoagulant use allowed at inclusion
|
Enzygnost TAT
Before chemotherapy
|
Screening for incident VTE with ultrasound after 1 month and if symptoms
VTE incidence: 10% (n = 12) within 3 mo FU
Type NR
|
TAT (↑) in VTE vs. non-VTE:
Mean 8.9 (CI: 2.4–32.5) vs. 5.7 µg/mL (4.0–8.0), p NS, value NR
|
|
Liang et al
2020[35]
Fair
|
Prospective observational
|
Cervical cancer patients admitted to hospital for treatment (n = 134)
Age: 51 y, range 30–73
Female: 100%
|
No anticoagulant use allowed at inclusion
|
HISCL5000
First day of admission
|
Examination for incident VTE with ultrasound
Timing NR
VTE incidence: 7% (n = 10)
Type NR
|
TAT ↑ in VTE vs. non-VTE:
3.28 ± 0.26 vs. 1.71 ± 0.14 ng/mL, (NR if means or medians), p = 0.004
|
|
Qi et al
2020[36]
Poor
|
Observational
retrospective
|
Solid cancer patients undergoing surgery (n = 286)
Age, VTE: 62 ± 5 y, non-VTE: 61 ± 5 y
Female: 45%
|
Patients in therapeutic doses excluded. Prophylaxis NR
|
Assay NR.
During hospital stay
|
Screening for incident VTE with ultrasound
Timing NR
22% (n = 63) VTE in 10 mo FU
All lower extremity DVT
|
TAT ↑ in VTE vs. non-VTE:
Mean 4.67 (SD ± 1.13) vs. 2.08 (± 0.75) µg/L, p = 0.036
In logistic regression per µg/L increase, RR = 6.122 (CI: 2.244–16.695)
ROC-curve AUC = 0.698, cutoff value 4.58 µg/L
|
|
Sallah et al
2004[30]
Good
|
Prospective observational
|
Solid cancer patients with diagnosis of first VTE (n = 223)
Age: 57 y (IQR NR)
Female: 50%
Site of cancer: Breast (20%), colorectal (16%), genitourinary (17%), head and neck
(14%), lung (18%) and other (15%)
|
All patients on VKA for at least 6 mo
|
TAT Antithrombin (Enzyme Research, Inc., South Bend, IN)
Before initiation of anticoagulation
|
VTE was an inclusion criterion for the study.
VTE recurrence confirmed by imaging
Incidence of recurrent VTE: 14% (n = 31)
Type NR
|
TAT ↑ in VTE vs. non-VTE:
Full cohort: Median 5.3 and mean 6.1 ng/mL
VTE recurrence cohort: Median 8.4 and mean 8.4 ng/mL
Univariate regression for VTE recurrence (cut-off NR): OR = 1.57 (CI: 1.09–2.27),
p = 0.01
|
|
Takata et al
2021[37]
Good
|
Retrospective
observational
|
Hepatocellular carcinoma patients undergoing hepatectomy (n = 65)
Mean age: 74 y ± 2 y
Female: 15%
|
Preoperative antithrombotic treatment (type NR) 14% of cohort (n = 9)
|
TAT Immunoassay (LSI Medience Corporation, Tokyo,
Japan)
Before surgery
|
Screening for portal vein thrombosis with CT before and 7 d after surgery
Portal vein thrombosis incidence: 20% (n = 13) in 7 d FU
|
TAT (↑) VTE vs. non-VTE[c]:
Before surgery: Mean 1.8 (SE ± 0.2) vs. 3.0 ng/mL (±0.4), p = 0.14.
Postoperative day 1: 20.2 ± 3.1 vs. 15.7 ± 1.6 ng/mL, p = 0.11
Postoperative day 2: 12.6 ± 1.8 vs. 11.9 ± 1.0 ng/mL, p = 0.63
Postoperative day 3: 11.4 ± 2.2 vs. 10.7 ± 0.8 ng/mL, p = 0.86
Risk of VTE based on ratio of TAT postoperative day 1 vs. preoperative, cut-off NR:
OR = 1.20 (CI: 1.01–1.42), p < 0.05.
ROC-curve on postoperative day 1 with cutoff 5.73 ng/mL: AUC = 0.786, p < 0.001
|
|
van Doormaal et al 2012[33]
Fair
|
Prospective observational
|
Mixed cancer patients (n = 43)
Age: 59 y ± 12 y
Female: 42%
Site of cancer: Breast (19%), gastrointestinal (37%), pancreatic (30%) and other (14%)
|
No anticoagulant use allowed at inclusion.
|
Enzygnost TAT
At inclusion
|
Symptomatic incident VTE confirmed with imaging during the FU period
VTE-incidence: 11.6% (n = 5) in 6 mo FU
PE (40%), DVT (40%) and other (20%)
|
TAT ↔ in VTE vs. non-VTE:
5.7 (IQR: 3.5–13.7) vs. 4.1 mg/L
(3.2–6.2), p = 0.29
|
Abbreviations: AUC, area under the curve; CI, 95% confidence interval; CT, computed
tomography; DVT, deep venous thrombosis; ELISA, enzyme-linked immunosorbent assay;
FU, follow-up; HR, hazard ratio; IQR, interquartile range; LMWH, low molecular weight
heparin; MRI, magnetic resonance imaging; NR, not reported; NS, nonsignificant, OR,
odds ratio, ROC, receiver operating characteristic, RR, relative risk, SD, standard
deviation, SE, standard error, TAT, thrombin-antithrombin complex, TF, tissue factor,
VTE, venous thromboembolic event(s).
Note: ↔ no change, ↑ increased, (↑) discreetly increased.
Note: Age and findings reported as median (IQR) unless stated otherwise.
a Study population part of the same cohort (the Vienna CATS-study).
b Study population part of the same cohort.
c Findings on postoperative day 1, 2, and 7 were read from Fig. 3 in publication.
Table 4
Studies measuring ex vivo thrombin generation
|
Author, year, quality assessment
|
Study design
|
Population
|
Thromboprophylaxis
|
Assay, sample timing
|
Outcomes, VTE definition and incidence
|
Findings
|
|
Abu Saadeh et al 2016[38]
Fair
|
Prospective observational
|
Ovarian or endometrial adenocarcinoma patients undergoing surgery (n = 96).
Age, VTE: 60 y (55–66)
Non-VTE: 58 (48–66)
Female: 100%
|
LMWH (Tinzaparin) 75 IU/kg daily for duration of hospital stay
|
Thrombinoscope
Before surgery
|
Incident symptomatic VTE, verified with imaging
VTE incidence: 8% (n = 8) in 180 d FU
PE (n = 3) and lower extremity DVT (n = 5)
|
TG (↑) in VTE (n = 5) vs. non-VTE (n = 43):
ETP: 1,928.2 (421.1) vs. 1,622.6 (475) nM x min, p < 0.05
Peak: 327.7 (73.1) vs. 288.8 (87.3) nM, p NR
ttPeak: 5.7 (1.9) vs. 6.57 (1.72) min, p NR
Lagtime: 3.01 (1.47) vs. 3.78 (1.6) min, p NR
|
|
Ay et al
2011[21]
Good
|
Prospective observational[a]
|
Mixed cancer patients (n = 1,033).
Age: 62 y (53–68).
Female: 55%
Site of cancer: Brain (13%), breast (15%), lung (14%), stomach (4%), colorectal (12%),
pancreas (7%), kidney (3%), prostate (12%), multiple myeloma (3%), lymphoma (12%)
and other (5%)
|
Short-term heparin prophylaxis allowed
|
Technothrombin
At inclusion
|
Incident symptomatic VTE, confirmed with imaging or autopsy
VTE incidence: 8% (n = 77) in 2 y FU
PE (43%), lower extremity DVT (13%) and other (44%)
|
TG ↑ in VTE vs. non-VTE:
ETP: 4.475 (IQR 4.087–4.915) vs. 4.386 (3.804–4.890) nM, p = 0.197
Peak: 556 (432–677) vs. 499 (360–603) nM, p = 0.14
ttPeak: 11.5 (9.5–14) vs. 13 (11–16) min, p = 0.006
Lagtime: 8 (7–10) vs. 9 (7–11) min, p = 0.036
Velocity index: 160 (111–223) vs. 127 (71–183) nM/min, p = 0.004
Cumulative risk of VTE in 6 mo for peak < 611 nM: 11% vs. 4%, p = 0.002
Multivariate, adjusted analysis, per 100 nM increase in peak:
HR = 1.15 (CI: 1.02–1.29), p = 0.019
Multivariate, adjusted analysis with 75th percentile cut-off (peak of 611 nM):
HR = 1.9 (1.2–3.0), p = .008
|
|
Chalayer et al
2019[39]
Good
|
Prospective observational
|
Newly diagnosed multiple myeloma patients undergoing first three cycles of chemotherapy
(n = 71).
Age: 67 y (59–73)
Female: 55%
|
Short-term heparin prophylaxis and fondaparinux allowed
|
Thrombinoscope
Before initiation of chemotherapy
|
Incident symptomatic arterial and VTE recorded at FU
VTE incidence: 11% (n = 8) in median 47 d
PE (25%), lower extremity DVT (62%), and other (13%)
|
TG ↔ in VTE vs. non-VTE:
Peak: 186 (120–218) vs. 149 (114–181) nmol/L, p = 0.22
ttPeak: 10.8 (7.3–11.3) vs. 9 (8.4–10.2) min, p = 0.82
|
|
Gezelius et al 2018[40]
Fair
|
Post-hoc of randomized controlled trial
|
Newly diagnosed small cell lung cancer patients undergoing chemotherapy (n = 242)
Mean age, intervention group: 66 y ± 8
Control group: 67 ± 9
Female: 57%
|
Intervention group (n = 115): LMWH (Enoxaparin) 1 mg/kg for duration of chemotherapy
Control group (n = 127): No prophylaxis
|
Thrombinoscope
Before initiation of chemotherapy
|
Clinical examination for incident VTE at 2-month intervals
VTE incidence, intervention group: 3% (n = 3)
VTE incidence, control group: 9% (n = 12)
Median FU time 276 days
Type NR
|
TG ↔ in VTE vs. non-VTE:
Peak: 236 (176–277) vs. 217 (176–261) nM, p = 0.42
ttPeak: 9.1 (7.4–11.2) vs. 10.0 (8.4–11.9) min, p = 0.26
ETP: 1,336 (1,164–1,471) vs. 1,222 (1,056–1,403) nM x min, p = 0.26
|
|
Leiba et al
2017[41]
Fair
|
Prospective observational
|
Multiple myeloma patients (n = 33).
Mean age: 63 y ± 9
Female: 47%
3 patients excluded from analysis due to VTE before sampling
|
Warfarin (n = 1, dose NR)
|
Thrombinoscope
Before therapy start
|
Imaging performed if clinical suspicion of VTE
VTE incidence: 24% (n = 8), mean FU 2.5 y
PE (25%), DVT (38%) and other (38%)
|
TG ↑ in VTE vs. non-VTE:
ETP: 2,896 vs. 2,028 nM x min, p < 0.001
Peak: 620 vs. 400 nM, p < 0.001
CI: NR
|
|
Posch et al
2016[28]
Good
|
Prospective observational[a]
|
Newly diagnosed or remitting cancer patients (n = 804)
Age: 63 y (54–69)
Female: 54%
Site of cancer: Brain (11%), breast (17%), gastrointestinal (18%), kidney (3%), lung
(15%), lymphoma (11%), other (8%), pancreas (7%), prostate (12%).
|
Anticoagulants not allowed
|
Technothrombin
At inclusion
|
Incident VTE detected by routine imaging or due to clinical suspicion
VTE incidence: 7% (n = 55) in 2 y FU
Type NR
|
TG ↑ in VTE vs. non-VTE:
Univariate risk score for VTE with 1 SD increase in peak: Subdistribution HR = 1.46
(CI: 1.08–1.87), p = 0.01
|
|
Reitter et al
2016[29]
Good
|
Prospective observational[a]
|
Solid cancer patients beginning chemo- or radiotherapy (n = 112)
Age: 62 y, range 21–80
Female: 43%
Site of cancer: Brain (35%), colorectal (13%), lung (37%) and pancreas (15%)
|
Short-term heparin prophylaxis allowed but NR
|
Technothrombin
At inclusion
|
Symptomatic VTE recorded and confirmed by imaging or autopsy report
VTE incidence: 13% (n = 14) in 250 days FU
PE (29%), DVT (50%) and other
|
TG ↔ in VTE vs. non-VTE:
HR per twofold increase in peak: 1.00 (CI: 0.99–1.00), p = 0.60
|
|
Schorling et al
2020[13]
Fair
|
Prospective observational
|
Ambulatory solid cancer patients starting chemotherapy (n = 100)
Age: 58 y (51–68)
Female: 62%
Site of cancer: Breast (30%), gastrointestinal (28%), genitourinary (16%), lung (4%),
pancreas (6%) and other (16%)
|
Anticoagulants not allowed
|
Thrombinoscope
Before therapy start
|
Symptomatic incident VTE and VTE discovered on routine imaging
VTE-incidence: 11% (n = 10) in 3 mo FU
PE + DVT (10%), PE (30%), DVT (50%), and other (10%)
|
TG ↔ in VTE vs. non-VTE:
VTE group:
Lagtime: 3.2 (1.8–5.8)
ttPeak: 6.7 min (4.1–10.4)
Peak: 260 nM (113–328)
ETP: 1,689 nM x min (1,240–1,860)
Non-VTE group
Peak: 379.9 nM, p = 0.005
ETP: < than VTE group, value NR, p = 0.036
Full cohort:
Lagtime: 2.2 min (1.5–3.0)
ttPeak: 4.5 min (3.7–5.7)
Peak: 364 nM (275–447)
ETP: 1,917 nM x min (1,659–2,354)
|
|
Syrigos et al
2018[42]
Good
|
Prospective observational
|
Ambulatory lung cancer patients (n = 150).
Mean age: 65 y ± 10
Female: 27%
|
Anticoagulants not allowed
|
Thrombinoscope
At inclusion
|
Symptomatic VTE, confirmed with imaging
VTE-incidence: 8% (n = 12) at 6 mo FU
PE (33%), DVT (58%) and other (8%)
|
TG ↑ in VTE vs. non-VTE:
OR (CI) for development of VTE (cut-offs NR):
Lagtime = 0.603 (0.294–1.235), p = 0.09
ttPeak = 0.522 (0.307–0.887), p = 0.09
Mean Rate Index = 1.016 (1.003–1.032), p = 0.02
Peak = 1.006 (0.997–1.016), p = 0.09
ETP = 1 (0.998–1.001), p = 0.1
|
|
Thaler et al
2014[31]
Good
|
Prospective observational[a]
|
Newly diagnosed high-grade glioma patients, 2–3 wk after surgery (n = 141)
Age: 54 y (44–64)
Female: 33%
|
Patients in therapeutic doses excluded. Prophylaxis 8–10 days post-surgery
|
Technothrombin
At inclusion
|
Symptomatic VTE confirmed by imaging or autopsy report
VTE incidence: 17% in 2 y FU (n = 24)
PE (46%), DVT (54%)
|
TG ↔ in VTE vs. non-VTE:
Peak for VTE group: 480 nM (263–670)
Peak for whole group: 432.8 nM (IQR: 192.8–597.0), p NR
HR for VTE development per 50 nM increase in peak:
Univariate HR = 1.04 (CI: 0.96–1.16), p = 0.311.
Multivariate HR = 1.03 (0.95–1.14), p = 0.451, both
|
|
Undas et al
2015[43]
Good
|
Prospective observational
|
Newly diagnosed multiple myeloma patients undergoing induction therapy (n = 48)
Age: 62 y (56–71)
Female: 63%
|
No anticoagulant treatment allowed prior to inclusion.
Aspirin or enoxaparin as thromboprophylaxis during chemotherapy (distribution NR)
|
Thrombinoscope
At inclusion
|
Symptomatic VTE confirmed with imaging during the FU period
VTE-incidence: 21% (n = 10) in 3 mo FU
PE (10%), DVT (90%)
|
TG ↑ in VTE[c] vs. non-VTE:
Peak: 503.5 (418–550) vs. 344.8 (269–411), p < 0.001
|
|
Yerrabothala et al
2021[46]
Fair
|
Prospective observational
|
Glioblastoma patients undergoing surgery (n = 20)
Mean age: 64 y, range 37–83
Female: 35%
|
No anticoagulant treatment allowed at inclusion
|
Thrombinoscope
At inclusion
|
Screening of medical records for incident VTE at FU
VTE-incidence: 10% (n = 2) in 6 mo FU
Type NR
|
TG ↑ in VTE vs. non-VTE:
Peak: Mean 364 nM vs. 290 nM, p = 0.04
|
Abbreviations: AUC, area under the curve; CI, 95% confidence interval; CT, computed
tomography; DVT, deep venous thrombosis; ELISA, enzyme-linked immunosorbent assay;
ETP, endogenous thrombin potential; FU, follow-up; HR, hazard ratio; IQR, interquartile
range; LMWH, low molecular weight heparin; MRI, magnetic resonance imaging; NR, not
reported; NS, nonsignificant; OR, odds ratio; PE, pulmonary embolisms; ROC, receiver
operating characteristic; RR, relative risk; SD, standard deviation; SE, standard
error; TF, tissue factor; TG, thrombin generation; ttPeak, time to peak; VTE, venous
thromboembolic event(s).
Note: Age and findings reported as median (IQR) unless stated otherwise.
Note: ↔ no change, ↑ increased, (↑) discreetly increased.
a Study population part of the same cohort (the Vienna CATS-study).
c Two patients who experienced an ischemic stroke have been included in this group,
alongside the 10 patients with VTE.
Fig. 2 Flow chart of the inclusion and exclusion process. TG, thrombin generation; VTE,
venous thromboembolic events. Figure created with BioRender.
Study Characteristics
Most studies were performed on patients with solid cancers (n = 17).[13]
[15]
[25]
[26]
[27]
[29]
[30]
[31]
[32]
[34]
[35]
[36]
[37]
[38]
[40]
[42]
[44] Studies on purely hematological cancer patients were few (n = 3).[39]
[41]
[43] The remaining four studies had mixed study groups.[19]
[21]
[28]
[33] All the included patients were adults. Mean follow-up times ranged from 7 days[25]
[37] to 2.5 years,[41] and most studies were prospective observational.
Two studies recorded recurrent VTE; in Sallah et al, VTE was an inclusion criterion
and thus all recorded VTE events were recurrent.[30] Tsubata et al screened for VTE at inclusion and allowed patients with a VTE to participate
in the study. They recorded both incidence and recurrence at 2 years follow-up.[32] The remaining studies excluded patients with prior recorded VTE events.
Seven studies were performed on cancer patients undergoing surgery[25]
[26]
[27]
[36]
[37]
[38]
[44] investigating postoperative VTE, and five studies were performed in cohorts where
>30% of the population underwent surgery.[19]
[21]
[30]
[34]
[35] In nine studies, all the patients received chemotherapy,[13]
[15]
[29]
[34]
[39]
[40]
[41]
[42]
[43] and in five, studies some patients received chemotherapy.[19]
[21]
[30]
[35]
[38] Thromboprophylaxis was allowed in 13 studies,[15]
[19]
[21]
[25]
[26]
[27]
[29]
[31]
[36]
[38]
[39]
[40]
[44] and therapeutic doses were allowed in four studies.[30]
[32]
[37]
[41]
In total, 10 out of 11 studies investigating F1.2 used the same enzyme immunoassay.
Most studies investigating TAT used the same enzyme immunoassay.[25]
[26]
[27]
[33]
[34] Two studies used an automated immunochemistry analysis[35] or a chemiluminescent immunoassay,[37] and the remaining two studies did not specify which assay they used.[30]
[36] Studies investigating thrombin generation utilized either the Calibrated Automated
Thrombogram (Thrombinoscope)[13]
[38]
[39]
[41]
[42]
[43]
[44]
[45] or the similar Thrombin Generation Assay (Technothrombin).[21]
[28]
[29]
[31]
Prothrombin Factor 1.2
Studies that were part of the Vienna CATS cohort generally found significantly increased
F1.2 levels in patients who later developed VTE[19]
[28]
[29]
[31] ([Table 2]). Ay et al found a median F1.2 in the patients who later developed VTE of 310 versus
249 pmol/L, yielding a hazard ratio (HR) of 2.0[19] (confidence interval [CI]: 1.2–3.6). These results were supported by Posch et al,[28] Reitter et al,[29] and Thaler et al,[31] who found HRs ranging from 1.48 to 2.11 for the development of VTE with F1.2 above
cut-off (p-values from <0.001–0.069).
The larger study by Iversen and Thorlacius-Ussing[27] (n = 137) did not find significantly elevated preoperative F1.2 levels in patients who
later developed a postoperative VTE, but the difference between the groups became
statistically significant on postoperative day 1 (p < 0.002) and day 2 (p < 0.01). In the smaller, initial study (n = 93) by the same authors no difference was demonstrated.[26] Tsubata et al[32] found significantly increased F1.2 levels in their VTE cohort, yielding an odds
ratio (OR) of 1.12 (CI: 1.073–1.169). However, this cohort included both incident
and recurrent VTE. The remaining four studies[15]
[25]
[30]
[33] found only weak and nonsignificant associations between F1.2 and the development
of CAT.
Thrombin-Antithrombin Complex
Three of the included nine studies found higher levels of TAT in patients who later
developed VTE[25]
[35]
[36] than in those who did not develop VTE ([Table 3]). Falanga et al[25] found 7.5 times increased relative risk (RR) of VTE in patients with a TAT > 3.5 ng/mL
(p < 0.01). Similar results were found by Qi et al,[36] where patients with increased TAT had an RR of 6.12 for the development of VTE (p-value not reported). Liang et al[35] did not calculate a risk estimate but found significantly elevated TAT levels in
their VTE cohort versus the patients who did not develop VTE. Sallah et al[30] investigated recurrent VTE and found an OR of 1.57 for VTE in their recurrence cohort
(p = 0.01). Similar to their findings on F1.2, Iversen et al[26]
[27] did not find an association between preoperative TAT levels and postoperative VTE
but did demonstrate an increased TAT on postoperative day 1 in VTE patients compared
to those that did not develop VTE ([Table 3]). Takata et al[37] had similar findings in their study on the incidence of portal vein thrombosis following
hepatectomy, finding a nonsignificant postsurgery spike in TAT ([Table 3]). The resulting OR for developing VTE with an increased TAT was 1.20 (cut-off NR,
CI: 1.01–1.42), p < 0.05). Finally, Kirwan et al and van Doormaal et al also found statistically nonsignificant
increased TAT levels in patients who later developed VTE.[33]
[34]
Ex Vivo Thrombin Generation
Four studies on ex vivo thrombin generation originated from the Vienna CATS cohort[21]
[28]
[29]
[31] ([Table 4]). Of these, the largest study by Ay et al[21] (n = 1,033) found the strongest association between thrombin generation and development
of VTE. They demonstrated overall increased thrombin generation in the VTE group,
demonstrated by decreased time to peak thrombin generation and lagtime as well as
an increased velocity index and peak thrombin in the patients who developed VTE versus
those who did not. This translated to an HR of 1.9 for VTE for peak thrombin values
greater than the 75th percentile, adjusted for age, sex, surgery, chemo- or radiation
therapy, tumor type, and stage (p = 0.008). These results were in line with Posch et al,[28] who found a 46% increased risk of VTE for 1 SD increase in measured peak thrombin
(n = 804, p = 0.01). The two smaller CATS studies[29]
[31] (n = 112 and n = 141) found no increased VTE risk associated with higher peak thrombin measurements.
Despite a small population size (n = 33), Leiba et al[41] demonstrated highly significant increased ETP of 2,896 versus 2,028 nM x min (p < 0.001) and peak thrombin of 620 versus 400 nM (p < 0.001) in multiple myeloma patients developing VTE. A similar result was found
by Undas et al,[43] who also investigated patients with multiple myeloma starting chemotherapy (peak
thrombin = 503.5 vs. 344.8, p < 0.001). The incidence of VTE was 21 to 24% in the two studies. Syrigos et al[42] found increased OR for the development of VTE in lung cancer patients with increased
thrombin generation, but only the mean rate index-based OR = 1.016 reached statistical
significance.
In the studies by Abu Saadeh et al[38] and Gezelius et al,[40] the cohort developing VTE had nonsignificantly increased thrombin generation. The
study by Chalayer et al[39] yielded conflicting, nonsignificant results with an increased peak thrombin in the
VTE group (186 vs. 149 nmol/L) but longer time to peak thrombin generation (10.8 vs.
9 minutes) in the same cohort. A similar result was found in the Schorling et al[13] study, where the VTE cohort had lower peak thrombin values (290 vs. 380 nM, p = 0.005) but higher ETP (values NR, p = 0.036) than the cohort without VTE.
Addition of Thrombin Generation Markers to Risk Assessment Scores
Pépin et al[15] investigated the addition of F1.2 measurements to the Khorana and Vienna CATS score.
Both scores were improved when F1.2 was added, with an OR of 5.7 for the Khorana score
and an OR 3.2 for the Vienna CATS score. When the authors added F1.2 and ADAMTS-13
to the CATS score, area under the receiver operator characteristics (AUROC) curve
improved from 0.56 to 0.71. Ay et al[19] found an HR of 2.0 (p = 0.02) for the development of VTE in patients with F1.2 above the 75th percentile
of the study population but did not apply this finding to an established risk assessment
score. Tsubata et al[32] developed a score including F1.2 and found this to be a better predictor of VTE
than fibrin D-dimer, with an AUROC curve of 0.75 (p < 0.001). Thaler et al[31] also developed a score, but neither peak thrombin generation nor F1.2 was a strong
enough predictor for VTE to be included. None of the included studies investigated
the addition of TAT to a risk assessment score.
The addition of mean rate index and procoagulant phospholipid-dependent clotting time
(Procoag-PPL) to the COMPASS-CAT score improved positive predictive value from 13
to 70%, sensitivity from 83 to 88%, and specificity from 51 to 70% in one study.[42] The negative predictive value was unchanged at 97%. By itself, the mean rate index
had an OR of 1.02 (p = 0.02).[42] Schorling et al[13] examined the Khorana, Vienna CATS, PROTECHT, ONKOTEV score, and Catscore, but found
no improvement by the addition of ex vivo thrombin generation parameters in their
cohort.
Discussion
Overall, the results from the present review presents evidence for the association
between elevated markers of thrombin generation and VTE in patients with cancer. We
chose to investigate F1.2, TAT, and ex vivo thrombin generation, as they all are well-established
markers of thrombin generation. Of these, F1.2 yielded the most consistent and convincing
result. Generally, studies with large cohorts demonstrated significantly elevated
F1.2 levels in patients who later developed VTE. The smaller studies with nonsignificant
findings pointed in the same direction but were probably underpowered to show significance.
This gives merit to the idea of including F1.2 in risk assessment scores to improve
sensitivity and/or specificity. Indeed, two of the included studies demonstrated an
improvement of the Khorana and Vienna CATS score when F1.2 was added.[15]
[32] Iversen et al. did not demonstrate a difference in their initial study obtaining
blood samples prior to surgery[26] but found significant differences in their later, larger study[27] on the same population also analyzing F1.2 levels on postoperative days 1 and 2.
Whether measurements taken after surgery may be better for risk assessment is an interesting
topic for future studies. Overall, F1.2 seems to be able to improve prediction of
VTE in larger cancer cohorts.
TAT was investigated in slightly fewer studies than F1.2. This, combined with greater
assay heterogeneity, makes results more explorative in nature. Overall, TAT seemed
to follow F1.2 and increase in patients at greater risk of VTE. Iversen and Thorlacius-Ussing[27] and Takata et al[37] reported greater difference in TAT levels between the patients who developed VTE
versus the patients who did not, on postoperative day 1 and 2 compared to the preoperative
sample. Like with F1.2, this seems justify a call for future studies examining the
importance of sample timing on VTE association in surgical cancer patients. Overall,
TAT seems to be elevated in patients developing VTE, though not as pronounced as F1.2.
Results on increased ex vivo thrombin generation and development of VTE in the included
studies were heterogenous. However, most included studies showed increased ex vivo
thrombin generation in cancer patients developing VTE. Thus, the overall results were
in line with those from F1.2 and TAT. Interestingly, two of the studies that found
strong associations between ex vivo thrombin generation and the development of VTE
were in cohorts of patients with multiple myeloma.[41]
[43] This may be due to a high VTE incidence in these two studies (21–24%).
Two studies found conflicting results, reporting lower ex vivo thrombin generation
in patients who later developed VTE.[13]
[39] In the study by Chalayer et al,[39] use of thromboprophylaxis was not found to be associated with any thrombin generation
parameter. The study by Schorling et al[13] did not allow use of anticoagulants. The authors conclude that ex vivo thrombin
generation may be less useful as a biomarker than F1.2 and TAT as the analysis only
displays the thrombin potential and not the actual in vivo turnover. Furthermore,
measurement of ex vivo thrombin generation is arguably less standardized than the
F1.2 and TAT assays. Overall, then, ex vivo thrombin generation seems to be a weaker
biomarker for VTE risk in cancer patients than F1.2 and TAT.
As evidenced in several studies, the risk of VTE is highly variable between different
cancer types and the prevalence of additional VTE risk factors such as age, sex, comorbidities
and treatment may also vary.[13]
[15]
[19] Thus, it is probably not feasible to develop a one-size-fits-all risk assessment
score, even with a score which takes the type of cancer into account in the points
assigned. Rather, scoring systems should be developed for specific cancer types or
groups.[43] If risk assessment scores are utilized in large diverse patient groups, it might
be prudent to aim to predict patients in low risk of VTE that thus might avoid thromboprophylaxis,
instead of aiming to identify high-risk patients.[31]
[34]
The included studies ranged quite widely in quality and comparability, which of course
impacts the validity of the overall findings of this review. However, despite this,
there is relatively high consensus in the findings which support the overall conclusions
drawn.
Some variability in sample processing and analysis between studies was noted. For
instance, Leiba et al[41] used a shorter centrifugation time, and Iversen et al[26]
[27] and Kirwan et al[34] utilized cooled centrifugation, which may impact results. However, the number of
commercially available assays are limited, and the analysis principles are largely
similar within the three analyses. Thus, there was an overall high degree of method
comparability within F1.2, TAT, and ex vivo thrombin generation studies which made
interstudy comparison possible and credible.
As evidenced in the included studies, the definition of VTE varied greatly.[31]
[37]
[42] Two studies included recurrent VTE.[30]
[32] Some studies included only symptomatic or accidentally discovered VTE and did not
screen the participants systematically. While this may be due to logistical or financial
considerations rather than a lack of interest in asymptomatic VTE, it makes results
in unscreened cohorts harder to interpret. However, the clinical significance of incidental
VTE is not fully understood. In the present review, the authors chose to exclude studies
accepting device-related and isolated superficial VTE as events. Arterial events were
also excluded, as the mechanisms behind arterial and venous thrombosis in cancer may
differ.[4] This choice was made in attempt to create a more homogenous population but of course
limits the conclusions in this review to venous thromboses.
The use of thromboprophylaxis was generally not well reported in the included studies,
and few studies reported on the proportion of patients receiving thromboprophylaxis
in the VTE versus non-VTE group or the mean duration of thromboprophylaxis. This made
it difficult to consider the influence of thromboprophylaxis on the reported associations,
especially for ex vivo thrombin generation. However, the included studies that allowed
anticoagulant treatment or prophylaxis generally also found a signification association
between markers of thrombin generation and development of VTE, thus strengthening
the evidence for the association.
Some of the included studies enrolled patients undergoing chemotherapy and/or surgery.
While this reflects a real-world cancer population, both chemotherapy and surgery
are known to affect coagulation and therefore may complicate result interpretation.
A variable proportion of the patients received anticoagulant treatment or prophylaxis
in the observation period.
The selected biomarkers are all reasonably replicable and can be used on stored samples.
This makes them more accessible for research as well as future routine implementation.
F1.2 and TAT may be easier to automate and incorporate in a routine laboratory setup
than ex vivo thrombin generation as they can be measured with widely available enzyme-linked
immunosorbent assay assays and results are reported as concentrations which simplifies
interpretation.[15]
