Cancer-Associated Thrombosis: Implications toward Health-Related Quality of Life

Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), represents a severe health problem associated with high morbidity and mortality among cancer patients. The annual incidence of VTE is estimated at around 1% in the general population.[1] Due to the hypercoagulable state in cancer patients, there is a fourfold to sevenfold increased risk of thrombosis.[1] VTE is also an independent risk factor for mortality in patients with cancer.[2] Cancer-associated thrombosis (CAT) is increasingly important due to the rising number of individuals living with cancer.

Generally, subcutaneous (SC) anticoagulants have been an ideal intervention for this population and are recommended as preferred therapy.[3] However, many studies had been performed over recent years to evaluate the use of newer direct oral anticoagulants (DOACs) with positive results. Despite extensive research, the risk of bleeding and CAT recurrence is observed in this population.[4] These outcomes and prolonged use of anticoagulants have a negative impact on patients' quality of life (QOL).[5] [6]

Although several studies have been published on health-related QOL (HRQOL) after DVT,[5] [6] [7] a minority were conducted within the cancer population. Little is known on how CAT will influence a cancer patient's QOL. The main goal of this study was to evaluate the HRQOL following CAT diagnosis and to investigate potential determinants of impaired HRQOL in cancer patients using EQ-5D-5L instruments.

This cross-sectional study was conducted in patients aged 18 years old and above, diagnosed and treated with either SC anticoagulants or DOACs for CAT at the Institut Kanser Negara (National Cancer Institute), Putrajaya, Malaysia, between November 2019 and May 2020. The study was approved by the Ministry of Health, and Malaysia Medical Research and Ethics Committee (MREC) (MREC-NMRR-19–565–45643). A random sampling was performed from the institutional registry of CAT patients scheduled for follow-up at the Oncology outpatient clinic. Participation was voluntary and written informed consent was obtained from all patients after being briefed regarding study objectives.

The QOL outcomes were measured by the EQ-5D utility index (−0.59 to 1.00) and the health status using EQ-VAS (0–100). The EQ-5D-5L was converted using the Malaysian EQ-5D value set calculator that was previously published by Shafie et al.[8] The mean value score of the two outcomes were 0.76 and 72.3, and were used as cut-off points to dichotomize the population into a high and a low group. Sociodemographic data, EQ-5D utility index and visual analogue status (EQ-VAS) were analyzed using Statistical Package for the Social Sciences (SPSS) software version 21 for descriptive, bivariate, and binary multiple logistic regression analyses.

A total of 80 patients consented and participated in this study, with mean age of 53.8 (±14.3) years at CAT diagnosis. The majority of participants were diagnosed with female reproductive organ cancer (30%), followed by colorectal and breast cancer. Moreover, 89% of participants had advanced or metastatic disease. Most of the patients were diagnosed with CAT within the first 6 months of a cancer diagnosis (58%). Eastern Cooperative Oncology Group (ECOG) performance status (PS) of 0 to 2 was recorded in 75% of participants. Nearly half of the patients had recurrent CAT (46%). The composite outcome of bleeding was documented in 15% of participants. The SC anticoagulants used in this study were enoxaparin, and fondaparinux, and the DOAC was rivaroxaban. [Table 1] demonstrates the sociodemographic characteristics of the study population.

Table 1 Demographic and baseline characteristics

Variables	Total (N = 80)
Age, years (mean, SD)	53.8 (14)
Women, n (%)	53 (66)
Weight, kg (mean, SD)	61.4 (15)
Ethnicity, n (%)
Malay	51 (64)
Non-Malay	29 (36)
Cancer diagnosis, n (%)
Gynecological	24 (30)
Colorectal	14 (17)
Breast	12 (15)
Lung	11 (14)
Germ cells	11 (14)
Others	8 (10)
Cancer stage (TNM), n (%)
Stage 1–2	9 (11)
Stage 3–4	71 (88)
ECOG performance status, n (%)
0–2	61 (75)
3–4	19 (25)
CAT, n (%)
Pulmonary embolism	26 (32)
Deep vein thrombosis	46 (57)
Both	8 (10)
Time to first CAT diagnosis, n (%)
< 6 mo	46 (57)
6–12 mo	10 (12)
> 12 mo	24 (30)
CAT recurrence, n (%)	34 (42)
Bleeding, n (%)	12 (15)

Abbreviations: CAT, cancer-associated thrombosis; ECOG, Eastern Cooperative Oncology Group; SD, standard deviation.

The most common problems related to QOL among patients with CAT were pain and/or discomfort (52%), followed by reduced mobility (45%) and impaired usual activity (45%) ([Table 2]). These results aligned with two previous studies, but these did not explicitly focus on cancer patients.[6] [9] The results of the current study concur with previous studies, which reported that cancer pain was associated with poor QOL and increased mood disturbance.[10] A numerically higher but not statistically significant proportion of patients had pain/discomfort when treated with SC anticoagulants compared with DOACs (56 vs. 49%). It is possible that SC anticoagulants were given with the intention that the anti-inflammatory effect of those agents might reduce the discomfort.[11]

Table 2 EQ-5D-5L descriptive system in each dimension

Dimension	No problem		Slight problem		Moderate problem		Severe problem		Extreme problem		All problems
	n	%	n	%	n	%	n	%	n	%	n	%
All patients diagnosed with cancer associated thrombosis (N = 80)
Mobility	44	55	13	16	13	16	9	11	1	1	36	45
Self-care	51	64	11	14	7	9	11	14	0	–	29	36
Usual activity	44	55	12	15	11	14	11	14	2	3	36	45
Pain/discomfort	39	49	28	35	10	13	4	5	0	–	42	53
Anxiety/depression	49	61	23	29	6	8	2	3	0	–	31	39
All patients diagnosed with cancer associated thrombosis that received direct oral anticoagulant (n = 41)
Mobility	23	56	7	17	7	17	3	7	1	2	18	44
Self-care	26	63	8	20	3	7	4	10	0	−	15	37
Usual activity	27	66	4	10	5	12	4	10	1	2	14	34
Pain/discomfort	21	51	17	42	3	7	0	–	0	–	20	49
Anxiety/depression	27	66	13	32	1	2	0	–	0	–	14	34
All patients diagnosed with cancer associated thrombosis that received subcutaneous anticoagulant (n = 39)
Mobility	21	54	6	15	6	15	6	15	0	–	18	46
Self-care	25	64	3	8	4	10	7	18	0	–	14	36
Usual activity	17	44	8	21	6	15	7	18	1	3	22	56
Pain/discomfort	17	44	11	28	7	18	4	10	0	–	22	56
Anxiety/depression	22	56	10	26	5	13	2	5	0	–	17	44

Abbreviation: EQ-5D−5L, Euro Quality of Life 5-dimension 5-level.

The mean score for the EQ-5D utility index and EQ-VAS health status in the current study was 0.76 (±0.3) and 72.3 (±17.9), respectively. The study's mean EQ-5D utility index and EQ-VAS health status were lower than the general Malaysian population (0.93, 82.22)[12] and Malaysian individuals with chronic myeloid leukemia (0.89, 81.95).[13] Our finding was in line with a previous report that confirmed the negative impact of CT on HRQOL among cancer patients.[14] Similar findings were also noted in populations without cancer.[5] [6] [14] [15] A study conducted on 883 patients found that CAT using the same instrument recorded a lower EQ-5D utility index than the present study.[16] This highlighted the importance of local data due to differences in response to the EQ-5D question between countries.

Interestingly, the EQ-5D utility index (0.8 ± 0.2 vs. 0.72 ± 0.3, p = 0.3) and EQ-VAS health status (75 ± 16.3 vs. 69 ± 19.3, p = 0.2) in patients receiving DOACs were similar to SC anticoagulants ([Table 3]). The utility index in this group of patients was comparable to individuals without cancer (0.8 vs. 0.79 vs. 0.81).[6] [15] This is to date the first study exploring the effects of DOACs on QOL specifically in cancer patients. This group of drugs offers benefits over traditional anticoagulants, such as non-requirement for routine laboratory monitoring and an attractive oral route of administration.

Table 3 Comparison of EQ−5D utility index and EQ-VAS health status in patients receiving SC anticoagulants or DOAC

	All patients	DOAC (n = 41)	SC anticoagulant (n = 39)	p-Value[a]
EQ-5D-5L utility index (Mean, SD)	0.76 (0.28)	0.80 (0.2)	0.72 (0.3)	0.3
EQ-VAS (mean, SD)	72.3 (17.9)	75 (16.3)	69.5 (19.3)	0.2

Abbreviations: DOAC, direct oral anticoagulant; EQ-5D-5L, Euro Quality of Life 5-dimension 5-level; SC, subcutaneous; SD, standard deviation; VAS, visual analogue scale.

^a Mann-Whitney U test.

We found that ECOG PS (adjusted odds ratio [OR] 0.03; 95% confidence interval [CI], 0.05–0.19) was a significant determinant of poor EQ-5D utility index among CAT patients ([Table 4]). This finding was in line with a former study by Lloyd and collegues.[16] However, it is essential to note that their study only included patients with an ECOG PS of 0 to 2. The current study included patients with poorer PS (up to ECOG PS 4) that are typically seen in the daily clinic. Patients with ECOG PS >2 were typically excluded from most randomized control trials; hence no comparison can be made with our study.

Table 4 Bivariate and binary logistic regression analysis of CT risk factor toward HRQOL EQ-5D utility index (n = 80)

Independent variables	HRQOL Utility value		X 2	p-Value[a]	OR (95% CI)	Wald	p-Value[b]	Adjusted OR (95% CI)
	Low (n, %)	High (n, %)
Gender  Men  Women	10 (37) 20 (38)	17 (63) 33 (62)	0.004	0.9	0.97 (0.37–2.53)	0.06	0.8	0.84 (0.21–3.39)
Ethnicity  Malay  Non-Malay	16 (31) 14 (48)	35 (69) 15 (52)	2.25	0.1	0.49(0.19–1.25)	4.754	0.03	0.22 (0.06–0.86)
Type of treatment used  SC anticoagulants  Rivaroxaban	16 (41) 14 (34)	23 (59) 27 (66)	0.404	0.5	1.34 (0.54–3.33)	0.004	0.9	0.96 (0.25–3.63)
ECOG performance status  0–2  3–4	14 (23) 16 (84)	47 (77) 3 (16)	23.19	<0.001	0.06 (0.01–0.22)	14.04	<0.001	0.03 (0.05–0.19)
Recurrence CT  Yes  No	17 (50) 13 (28)	17 (50) 33 (72)	3.94	0.047	2.54 (1.00–6.43)	3.77	0.05	4.09 (0.99–16.94)
Bleeding  Yes  No	7 (58) 23 (34)	5 (42) 45 (66)	2.61	0.1	2.74 (0.78–9.59)	0.02	0.8	1.14 (0.18–7.29)
Cancer Stage  Locally – locally advanced  Metastatic	5 (17) 25 (49)	24 (83) 26 (51)	7.97	0.005	0.22 (0.07–0.66)	2.15	0.1	0.33 (0.73–1.46)
Pulmonary Embolism  Yes  No	14 (47) 16 (53)	12 (24) 38 (76)	4.39	0.036	2.77 (1.05–7.29)	2.52	0.1	9.12 (0.59–139.79)
Deep vein thrombosis  Yes  No	14 (47) 16 (53)	32 (64) 18 (36)	2.31	0.1	0.49 (0.19–1.24)	1.13	0.3	4.57 (0.28–75.39)

Abbreviations: CI, confidence interval; CAT, cancer-associated thrombosis; ECOG, Eastern Cooperative Oncology Group; HRQOL, health-related quality of life; OR, odds ratio; SD, standard deviation.

Note: p-Values significant at p <0.05.

^a Pearson Chi-square.

^b Binary logistic regression.

It is important to note that 88% of our patients were diagnosed with advanced/metastatic disease. Poor PS was more frequently seen in patients with advanced/metastatic disease. Previous studies have identified that patients with advanced/metastatic disease have worse symptoms, function scores, and poor-quality disease than patients with early status disease.[17] This could be because patients with higher PS would have reduced physical activity and be confined to bed. They are also more bothered by problems related to their physical and mental functions.

On the other hand, bleeding was not found as a determinant of poorer HRQOL as opposed to what was reported in some studies involving patients without cancer.[14] [15] However, we found that CT recurrence (adjusted OR 4.09; 95% CI, 0.99–16.9) was a significant determinant of poorer HRQOL. A similar negative impact of CT recurrence was seen in a previous study in cancer patients.[16] These findings were not seen in the non-cancer population due to the lower rate of recurrence of thrombosis (1%) seen in their study population using similar questionaires.[14] [15] In our study, nearly half (42.5%) of the patients experienced CAT recurrence. Therefore, with the considerable incidence of recurrent CAT detected in this study, the relationship between recurrent CAT with poor HRQOL could be detected ([Table 4]). A similar result was observed in a study by van-Korlaar and colleagues[7] whereby they found that multiple thrombotic events were associated with impaired HRQOL. However, it should be noted that the reported scores were not directly comparable since they were using SF-36 scores in patients without cancer.

In terms of EQ-VAS health status, there were two significant determinants of poorer EQ-VAS scores: men (adjusted OR 5.40; 95% CI, 1.54–19.01) and poorer ECOG PS (adjusted OR 0.21; 95% CI, 0.06–0.78) ([Table 5]). No direct comparison could be made with prior studies since most of them were conducted in patients without cancer. However, compared with the latter population, some discrepancies were observed where women were reported to have poorer HRQOL than men.[9] A similar study conducted using EQ-5D also found that women with cancer had poorer HRQOL than men.[16]

Table 5 Bivariate and binary logistic regression analysis of CAT risk factor toward EQ visual analogue scale (EQ-VAS) health status (n = 80)

Independent variables	VAS health status		X 2	p-Value[a]	OR (95% CI)	Wald	p-Value[b]	Adjusted OR (95% CI)
	Low	High
Gender  Men  Women	17 (63) 19 (36)	10 (37) 34 (64)	5.31	0.02	3.04 (1.16–7.96)	6.90	0.009	5.40 (1.54–19.01)
Ethnicity  Malay  Non-Malay	26 (51) 10 (34)	25 (49) 19(66)	2.03	0.2	1.98 (0.77–5.07)	1.41	0.2	2.00 (0.64–6.28)
Type of treatment used  SC anticoagulant  Rivaroxaban	19 (48) 17 (41)	20 (52) 24 (59)	0.425	0.5	1.34 (0.55–3.24)	0.03	0.7	1.10 (0.38–3.17)
ECOG  0–2  3–4	23 (38) 13 (68)	38 (62) 6 (32)	5.52	0.019	0.28 (0.09–0.84)	5.44	0.020	0.21 (0.06–0.78)
Recurrence CT  Yes  No	19 (56) 17 (37)	15 (44) 29 (63)	2.83	0.1	2.16 (0.88–5.33)	1.27	0.3	1.92 (0.62–5.97)
Bleeding  Yes  No	5 (42) 31 (46)	7 (58) 37 (54)	0.063	0.8	0.85 (0.25–2.96)	1.56	0.2	0.35 (0.07–1.82)
Cancer stage  locally advanced  metastatic	10 (34) 26 (51)	19 (66) 25 (49)	2.03	0.2	0.51 (0.19–1.30)	1.36	0.2	0.48 (0.14–1.64)
Pulmonary embolism  Yes  No	15 (58) 21 (39)	11 (42) 33 (61)	2.51	0.1	2.14 (0.83–5.55)	3.16	0.1	7.62 (0.81–71.43)
Deep vein thrombosis  Yes  No	19 (41) 17 (50)	27 (59) 17 (50)	0.59	0.4	0.70 (0.29–1.72)	1.18	0.3	3.36 (0.38–29.76)

Abbreviations: CAT, cancer-associated thrombosis; OR, odds ratio; SC, subcutaneous; SD, standard deviation; VAS, visual analogue scale.

Note: p-Value significant at p < 0.05.

^a Pearson Chi-square.

^b Binary logistic regression.

We used EQ-5D-5L for several reasons. First, it has been validated in the Malaysian population.[12] Second, it was recommended by health technology assessment agencies.[8] Third, it directly provides the utility index that is much needed for cost-utility analysis. Finally, other instruments were much lengthier to assess, and thus, can be a burden to patients.[12]

One study strength was that real-world patients were recruited with more lenient inclusion and exclusion criteria to represent daily clinical practices. Nonetheless, it is essential to note some limitations in this study. The constraints of collecting data at a single national cancer center with a few respondents limit the generalizability. However, being a national center, different types of patients were included from every part of Malaysia. The study was conducted with cancer patients; therefore, it has the risk of confounding effects from cancer itself. Consequently, it is essential to highlight that the result of this study should be interpreted cautiously.

In conclusion, this study demonstrated that the overall HRQOL of CAT patients was lower than in the general population. Significant determinants, such as men, poorer ECOG PS, and CAT recurrence were associated with worse HRQOL. Recurrent CAT is a modifiable determinant, highlighting the importance of effective prophylaxis. Larger studies are needed to evaluate the best treatment strategy.

Publication History

Article published online:
30 June 2022

• References

• 1 Dhami SPS, Patmore S, O'Sullivan JM. Advances in the management of cancer-associated thrombosis. Semin Thromb Hemost 2021; 47 (02) 139-149
• 2 Prandoni P, Lensing AW, Piccioli A. et al. Recurrent venous thromboembolism and bleeding complications during anticoagulant treatment in patients with cancer and venous thrombosis. Blood 2002; 100 (10) 3484-3488
• 3 NCCN clinical practice guidelines in oncology (NCCN Guidelines); Guidelines for cancer-associated venous thromboembolic disease Version 2. 2021 . Accessed June 15, 2021 at: nccn.org/professionals/physician_gls/pdf/vte.pdf
• 4 Al-Samkari H, Connors JM. Managing the competing risks of thrombosis, bleeding, and anticoagulation in patients with malignancy. Blood Adv 2019; 3 (22) 3770-3779
• 5 Kahn SR, Ducruet T, Lamping DL. et al. Prospective evaluation of health-related quality of life in patients with deep venous thrombosis. Arch Intern Med 2005; 165 (10) 1173-1178
• 6 Utne KK, Tavoly M, Wik HS. et al. Health-related quality of life after deep vein thrombosis. Springerplus 2016; 5 (01) 1278
• 7 van Korlaar IM, Vossen CY, Rosendaal FR. et al. The impact of venous thrombosis on quality of life. Thromb Res 2004; 114 (01) 11-18
• 8 Shafie AA, Vasan Thakumar A, Lim CJ, Luo N, Rand-Hendriksen K, Md Yusof FA. EQ-5D–5L Valuation for the Malaysian population. Pharmacoeconomics 2019; 37 (05) 715-725
• 9 König HH, Bernert S, Angermeyer MC. et al; ESEMeD/MHEDEA 2000 Investigators. Comparison of population health status in six European countries: results of a representative survey using the EQ-5D questionnaire. Med Care 2009; 47 (02) 255-261
• 10 Oliveira KG, von Zeidler SV, Podestá JRV. et al. Influence of pain severity on the quality of life in patients with head and neck cancer before antineoplastic therapy. BMC Cancer 2014; 14: 39
• 11 Mousavi S, Moradi M, Khorshidahmad T, Motamedi M. Anti-inflammatory effects of heparin and its derivatives: a systematic review. Adv Pharmacol Sci 2015; 2015: 507151
• 12 Shafie AA, Hassali MA, Liau SY. A cross-sectional validation study of EQ-5D among the Malaysian adult population. Qual Life Res 2011; 20 (04) 593-600
• 13 Wan Puteh SE, Aizuddin AN, Tumian NR, Sathar J, Mohamad Selamat E. Health-related quality of life using EQ-5D among chronic myeloid leukaemia patients in health centres in Klang Valley, Malaysia. PLoS One 2021; 16 (08) e0256804
• 14 Chuang LH, Gumbs P, van Hout B. et al. Health-related quality of life and mortality in patients with pulmonary embolism: a prospective cohort study in seven European countries. Qual Life Res 2019; 28 (08) 2111-2124
• 15 Hogg K, Kimpton M, Carrier M, Coyle D, Forgie M, Wells P. Estimating quality of life in acute venous thrombosis. JAMA Intern Med 2013; 173 (12) 1067-1072
• 16 Lloyd AJ, Dewilde S, Noble S, Reimer E, Lee AYY. What impact does venous thromboembolism and bleeding have on cancer patients' quality of life?. Value Health 2018; 21 (04) 449-455
• 17 Oates J, Davies S, Roydhouse JK, Fethney J, White K. The effect of cancer stage and treatment modality on quality of life in oropharyngeal cancer. Laryngoscope 2014; 124 (01) 151-158