Abstract
Objectives
Lung cancer is strongly associated with venous thromboembolism (VTE), but primary prevention against VTE is not a validated management strategy. Risk assessment models will be necessary for efficient implementation of preventative strategies.
Materials and methods
Utilizing a prospectively collected lung cancer database, we aimed to validate the Khorana Risk Score (KRS) in the prediction of VTE among patients with lung cancer. VTE events were retrospectively identified by reviewers unaware of the clinical prediction score calculation. The association between KRS and the risk of VTE was examined using cumulative incidence function with competing risks models. Mortality prediction was evaluated as secondary outcome.
Results
We included 719 patients in our review. The patients were predominantly older males with NSCLC and 40% had metastatic disease at inception. The median follow up was 15.2 months. There were 83 VTEs (11.5%) and 568 (78.8%) patients died. A high KRS (Cumulative Incidence 12.4%, 95% Confidence Interval 6.4-20.5%) was not associated with VTE compared to an intermediate score (Cumulative Incidence 12.1%, 95% Confidence Interval 9.5-15.0%)) in both univariate and multivariable analyses. However, a high KRS was a predictor of mortality (HR 1.7 95% CI 1.4 - 2.2).
Conclusions
Among patients with lung cancer the KRS did not stratify the patients at the highest risk of VTE. Improved risk stratification methods are needed for this group of patients prior to implementing a primary prevention strategy.
Keywords: Lung Cancer, Venous Thromboembolism, Prediction Score, Mortality, Prevention
INTRODUCTION
Lung cancer is the second most common cancer in United States. Lung Cancer is also strongly associated with venous thromboembolism (VTE). As noted in a 13-year period study in the Olmsted County, Minnesota population, the standardized risk of VTE among patients with lung cancer is 13 times higher than expected [1]. VTE is a morbid, costly and potentially lethal complication among patients with cancer [2]. Indeed, cancer-associated thrombosis is a leading cause of death among patients with cancer [3]. Patients with lung cancer and early occurrence of VTE, have a worse survival than patients who do not develop VTE even after adjusting for stage, comorbidities, performance status [4]. Cancer-associated thrombosis is a potentially preventable disease, however primary prevention is not currently a validated strategy [5]. The implementation of risk assessment models for VTE risk stratification may improve the applicability of primary prevention strategies in this population.
Assessment of VTE risk is currently recommended before initiation of chemotherapy [6]. To date, the best validated cancer-associated thrombosis prediction score is the Khorana risk score (KRS) [7]. The score is heavily weighted on type of cancer, thus all patients with lung cancer have at least intermediate risk. Save-ONCO studied the use of semuloparin for primary VTE prevention in 3212 patients with cancer, and lung cancer was the most common type of malignancy that was included (36%). In this study the KRS failed to predict most of the thromboembolic events, and most of the cancer-associated thromboses occurred among patients with an intermediate KRS (64%) [8, 9]. If the KRS does not perform well among patients with one of the most common types of cancer, this group of patients will need a cancer-specific evaluation of VTE predictors. We aimed to evaluate the performance of the KRS for cancer-associated VTE prediction in a cohort of patients with lung cancer.
POPULATION AND METHODS
We used a prospectively maintained database of consecutive patients with lung cancer treated at Mayo Clinic Rochester between January 1998 to December 2011. The primary outcome was VTE prediction and the secondary outcome was overall survival prediction. All cases were histologically examined by a Mayo Clinic pathologist. Demographic variables and cancer specific variables including performance status, stage, grade, cell type were prospectively collected. Patients on chronic anticoagulants were excluded from the analysis. For patients diagnosed after January 2010, the 7th edition of lung cancer staging system was used [10]. The data for the KRS correspond to clinical data obtained within 1 month of recruitment, including blood counts. The KRS was retrospectively quantified based on corresponding clinical-pathological variables (1 point each for lung cancer; BMI ≥35; Hemoglobin < 10g/dL or erythropoietin stimulating agent; white blood cells ≥ 11, 000; platelets ≥ 350,000). The primary outcome measure was VTE, including symptomatic or incidentally found deep vein thrombosis (DVT) of lower or upper limbs, pulmonary embolism (PE) and visceral venous thrombosis. Incidental VTE was defined as those were detected in the absence of a documented clinical symptom. VTE was retrospectively extracted from the electronic medical records by two of the coauthors (EW, TK) who were unaware of the clinical prediction score calculation. The VTE diagnosis was assigned based on pre-defined criteria: limb or visceral VTE confirmed by venogram, angiography, computed tomography, magnetic resonance, or compression ultrasound. Overall survival follow up was available for all patients. Time to death and time to VTE from recruitment date were determined for all cases. The Mayo Foundation Institutional Review Board approved this study.
Statistical analysis
We calculated descriptive statistics to summarize the distribution of baseline parameters. Continuous measures were categorized into quartiles to explore their association with the outcomes of interest [11, 12]. We included height among the VTE predictors due to recent data that underscored an independent association with thrombotic events[13]. The association between KRS and the risk of VTE was analyzed using cumulative incidence function with competing risk models as proposed by Fine and Gray[14]; while the association between KRS and the hazard of death was examined using Kaplan-Meier survival curve and Cox proportional hazards regression modelling. A high score was defined as ≥ 3 [7]. We did not model for missing information, only available data were analyzed. All-cause mortality was studied as a secondary outcome. Multivariable analyses were done using forward modeling and limited given number of events. For all statistical analyses we used SAS 9.4 (SAS Institute Inc., Cary, NC, USA). Non-parametric continuous variables are expressed as median and inter quartile rage (IQR). A p value of <0.05 was considered as statistically significant.
RESULTS
From a total of 727 patients with lung cancer, we included 719 patients in this analysis as eight patients had prior VTE and were excluded. The patients in this study were predominantly older (median 68 years), males (52% of patients), with NSCLC (87%), and metastatic disease (40.5%) (Table 1). The median follow up was 15.2 months (IQR 4.6 – 42.4). There were a total of 83 VTEs (11.5% of patients) and 568 (78.8%) patients died. Twelve patients had incidental VTE. The location of the VTE was PE for 30 patients, isolated lower extremity DVT for 31 patients, DVT and PE for 4 patients, upper extremity DVT for 14 patients and visceral for 4 patients. KRS was calculated for all but 61 patients of the total cohort (incomplete data available to calculate score). Thus, four patients with VTE had an undetermined KRS. The main reason for having an incomplete score was missing a CBC value within 1 month of recruitment. One hundred patients (15% of 658 patients with calculable KRS) had a high KRS. None of the patients were on erythropoietin stimulating agents. Only 42 patients (5.8% of total cohort) had a BMI ≥ 35.
Table 1. Sample characteristics of 719 lung cancer patients.
| Characteristics | N | % |
|---|---|---|
| Demographic Variables | ||
| *Age (year) | 68.2 | 11.0 |
| Gender (Female) | 348 | 48.4 |
| *Height (m) | 1.7 | 0.1 |
| *Weight (kg) | 74.5 | 18.2 |
| *BMI (kg/m2) | 26.1 | 5.6 |
| Comorbidity Variables | ||
| Myocardial Infarction | 74 | 10.4 |
| Heart Failure | 41 | 5.7 |
| Dementia | 8 | 1.1 |
| Renal disease | 38 | 5.3 |
| COPD | 243 | 33.8 |
| Autoimmune disease | 33 | 4.6 |
| Liver disease | 7 | 0.9 |
| Diabetes | 92 | 12.9 |
| CVA/ TIA | 46 | 6.4 |
| *Hemoglobin (g/dL) | 12.6 | 1.8 |
| *Platelets (000/mL) | 289.5 | 115.2 |
| *White blood cells (000/mL) | 9.7 | 4.1 |
| Aspirin | 318 | 44.9 |
| ACE / ARB | 146 | 20.6 |
| Cancer Specific Variables | ||
| SCLC | 93 | 12.9 |
| - Extensive | 63 | 67.7 |
| NSCLC | 626 | 87.1 |
| - Stage Ia | 148 | 20.6 |
| - Stage Ib | 67 | 9.3 |
| - Stage IIa | 10 | 1.4 |
| - Stage IIb | 22 | 3.0 |
| - Stage IIIa | 73 | 10.2 |
| - Stage IIIb | 68 | 9.5 |
| - Stage IV | 220 | 30.6 |
| - Unknown/missing | 18 | 2.5 |
| High grade | 208 | 28.9 |
| Metastatic | 291 | 40.5 |
| Treatment Variables | ||
| Surgery | 271 | 37.7 |
| Radiation | 181 | 25.2 |
| Chemo | 270 | 37.6 |
| Khorana Score Variables | ||
| BMI ≥ 35 kg/m2 | 42 | 6.1 |
| Hemoglobin < 10 g/dL | 48 | 7.33 |
| WBC ≥ 11 000/ mL | 174 | 26.6 |
| Platelets ≥ 350 000/mL | 154 | 23.6 |
| Khorana score Intermediate (≤2) | 558 | 84.8 |
| Khorana score High (≥3) | 100 | 15.0 |
| Outcome Variables | ||
| VTE | 83 | 11.5 |
| Death | 568 | 78.8 |
| ^Follow up (month) | 15.2 | 4.6 – 42.4 |
presented as mean and standard deviation, ^ median and inter quartile range.
Eighty-five percent of the VTE events occurred among patients with intermediate KRS. A high score was not associated with a higher risk for VTE compared to an intermediate score (Figure 1). The overall cumulative incidence of VTE for high and intermediate KRS were 12.4% (95%CI 6.4-20.5) and 12.1% (95%CI 9.5-15.0), prospectively (p=0.2101). The cumulative incidence of VTE at 3, 6, 12, and 24 months were 5.2%, 6.2%, 7,2%, and 10.3% for high KRS and 5.1%, 6.3%, 7.4%, and 9.2% for intermediate KRS (Table 2). These differences were not statistically significant. High platelet count was the only component of the KRS construct that was predictive of VTE (HR 2.3; 95%CI 1.4 –3.8). Comorbidities associated with VTE in the univariate analysis were history of stroke and ASA (Table 2). Height was explored by gender; the 75th percentile of height was 182 cm for males (median 175 cm, IQR 170-182) and 165 cm for females (median 161 cm, IQR 157 - 165). Male gender and younger age was associated with higher risk of VTE, but not height. Grade, metastatic disease, cell type were not predictors of VTE. In the multivariable analysis, only surgery (HR 0.35; 95%CI 0.18-0.68) and chemotherapy (HR 2.2; 95%CI 1.2-4.3) were independent predictors of cancer-associated VTE in lung cancer. Among patients with NSCLC, there was no significant association of a high KRS and VTE. KRS was a predictor of mortality (HR 1.7 95% CI 1.4 - 2.2) in this cohort of patients with lung cancer (Figure 2). These results remained statistically significant after controlling for metastatic disease, age and cancer type.
Figure 1. Cumulative incidence of VTE by lung cancer patients with high Khorana risk score (solid line) and intermediate Khorana risk score (dotted line).
Table 2. Univariate analysis of VTE rate by presence of risk factor and the cumulative incidence estimates at 3, 6, 12, and 24 months.
| Risk Factor | Cumulative Incidence of VTE (%)* | p value |
|||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| With risk factor | No risk factor | ||||||||||
| 3 mo |
6 mo |
12 mo |
24 mo |
Overall | 3 mo |
6 mo |
12 mo |
24 mo |
Overall | ||
| Demographics | |||||||||||
| Age > 76yo | 2.9 | 3.0 | 3.6 | 4.2 | 6.6 | 5.3 | 6.6 | 8.4 | 10.3 | 13.2 | <.0001 |
| Male | 4.9 | 6.3 | 8.7 | 10.1 | 12.8 | 4.7 | 5.2 | 5.8 | 7.5 | 10.5 | 0.006 |
| Taller patients (≥75% tile) | 7.3 | 8.4 | 10.1 | 10.6 | 11.7 | 4.2 | 5.1 | 6.1 | 8.1 | 11.6 | 0.742 |
| Comorbidities | |||||||||||
| Hx of MI | 5.7 | 7.1 | 8.6 | 8.6 | 11.4 | 4.7 | 5.7 | 7.1 | 8.8 | 11.8 | 0.520 |
| Heart Failure | 2.6 | 5.1 | 5.1 | 5.1 | 10.3 | 4.9 | 5.8 | 7.3 | 8.9 | 11.8 | 0.139 |
| Dementia | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 4.9 | 5.9 | 7.2 | 8.9 | 11.9 | 0.205 |
| COPD | 4.2 | 5.1 | 7.1 | 7.6 | 12.7 | 5.1 | 6.1 | 7.4 | 9.3 | 11.2 | 0.827 |
| CVA/ TIA | 2.3 | 2.3 | 2.3 | 2.3 | 2.3 | 5.0 | 6.0 | 7.5 | 9.2 | 12.4 | 0.029 |
| ASA | 3.5 | 4.8 | 5.8 | 6.4 | 8.0 | 5.9 | 6.9 | 8.7 | 11.1 | 14.9 | 0.018 |
| Treatment Variables | |||||||||||
| Surgery | 2.2 | 2.6 | 3.0 | 3.3 | 8.6 | 5.9 | 7.6 | 9.7 | 11.7 | 13.2 | <.0001 |
| Radiation | 5.6 | 7.2 | 8.9 | 10.6 | 13.3 | 3.5 | 4.9 | 5.8 | 7.0 | 10.2 | <.0001 |
| Chemo | 5.9 | 8.6 | 11.5 | 13.8 | 17.1 | 2.6 | 2.6 | 2.9 | 3.5 | 6.5 | <.0001 |
| Khorana Score Variables | |||||||||||
| BMI ≥ 35 kg/m2 | 7.3 | 7.3 | 7.3 | 9.8 | 14.6 | 4.8 | 5.8 | 7.0 | 8.8 | 11.4 | 0.744 |
| Hemoglobin < 10 g/ dL | 0.0 | 0.0 | 0.0 | 0.0 | 2.3 | 5.5 | 6.6 | 8.1 | 9.9 | 12.9 | 0.035 |
| Platelets ≥ 350 000/ mL | 7.3 | 8.6 | 10.6 | 13.9 | 14.6 | 4.4 | 5.6 | 6.9 | 8.1 | 11.5 | 0.027 |
| WBC ≥ 11 000/mL | 2.9 | 3.5 | 5.2 | 6.4 | 9.3 | 5.7 | 7.2 | 8.4 | 10.3 | 13.1 | 0.226 |
Accounting for competing risk of mortality
Figure 2. Kaplan-Meier plot of overall survival by lung cancer patients with high risk Khorana score (solid line) and intermediate Khorana risk score (dotted line).
DISCUSSION
In this prospectively maintained cohort of patients with lung cancer and retrospectively adjudicated VTE events, a high KRS was not predictive of thrombotic events but was independently associated with all-cause mortality. The KRS was initially described using the Awareness of Neutropenia in Chemotherapy Study Group Registry. Among 4066 patients with a median follow up of 73 days, 2701 were used for the derivation cohort. In the derivation group, 554 patients (20.5%) had lung cancer and 60 patients developed a VTE. In the validation cohort of this study, the score had a very high negative predictive value (98.5%), but a positive predictive value of less than 7% [7]. Therefore the KRS performs best defining the population at low risk of VTE but it is not surprising that in a population of patients with higher VTE probability the score does not perform well. Similarly, in the SAVE ONCO trial, among patients with a high KRS only 4 of 301 patients in the placebo arm and 3 of 313 patients on the semuloparin arm developed a VTE [9]. In our study most of the VTEs (85%) occurred in the intermediate risk group. In the Vienna CATS (cancer associated thrombosis study), in a cohort of 819 patients with cancer, 61 developed an incident VTE. A high KRS predicted 26% of the events, but again most of the events occurred in patients at intermediate risk [15].
Our findings are consistent with those of others and stress the need of improved stratification methods for cancer-associated VTE prediction among patients in types of cancer with high risk of thrombosis. In a randomized controlled trial using dalteparin for the prevention of VTE among 2202 patients with lung cancer who were randomized over 4 years to dalteparin or placebo, there were 78 (7.1%) confirmed VTEs in the control group and 47 (4.1%) in the treatment group; however, no mortality benefit was confirmed with prophylactic anticoagulation [16] . Although prophylaxis is effective, administration of low molecular weight heparin without risk stratification does not seem to be helpful.
A BMI ≥ 35 was unusual in our cohort as has been seen in other series of patients with lung cancer [17]. It is plausible that the low prevalence of this variable decreases the validity of its use in the score. The PROTECHT study was a randomized trial that tested the use of nadroparin versus placebo for outpatient cancer-associated VTE prevention [18]. Among 378 patients in the placebo group only 1.3% had a BMI ≥ 35, thus it did not add value to the thromboembolic risk prediction [18].
We are not first to describe the KRS as a potential predictor of mortality. In a study of patients with pancreatic cancer, patients with a high KRS were more likely to die within 6 months (HR 2.5; 95%CI 1.1 – 2.1) [19]. Similarly, in a prospective cohort of 1544 patients with different types of cancer the KRS was associated with risk of death (HR per increase of 1 point within KRS: 1.6; 95%CI 1.45–1.68). [20]. We have now validated this finding among patients with lung cancer.
The main strength of our study is that this derives from a large prospective lung cancer database. The cancer-specific variables were prospectively collected allowing for accuracy in our analysis. This database however was not created for VTE evaluation. Thus there were patients without a complete KRS score. These data were assumed to be missing without a specific missingness mechanism. Therefore we only conducted a complete-case-analysis. Another limitation was that like any other retrospective study, we did not conduct a formal power analysis. Therefore, our study might be underpowered to draw firm conclusions about the association between KRS and risk of VTE though the cumulative incidence estimate was very similar between high and intermediate KRS groups. Furthermore, the adjudication of VTE was retrospective, thus it is plausible some cases were not represented despite the robust electronic medical records system and extensive follow up as patients received the majority of their care at Mayo Clinic. The chart reviewers had no data on the KRS, thus we do not anticipate there was a systematic assignment of VTE relative to the risk score. Autopsies were not performed for all patients, therefore it is plausible that some of the deaths were due to fatal PE and captured by the KRS. Furthermore, we used values obtained from CBC at baseline, not those obtained subsequent to chemotherapy, which is reflective of how the KRS was derived [7]. For the patients who received chemotherapy, the values of the CBCs likely changed with time and diluted the adverse association of WBC and platelet count with an increased risk of VTE.
In conclusion, the KRS did not accurately identify patients with a high risk for VTE but was a predictor of lung cancer mortality. Our findings stress the need for cancer specific risk assessment for VTE prediction.
Essentials.
Venous thromboembolism (VTE) prevention strategies require effective risk assessment models.
We sought to validate the Khorana Risk Score (KRS) in patients with lung cancer.
A high KRS was not predictive of VTE but was independently associated with all-cause mortality.
Our findings stress the need for a lung cancer-specific VTE risk assessment model.
Acknowledgement
We would like to acknowledge Bobbi-Ann Jebens and Yi Wang for their assistance.
This work was supported by National Institutes of Health [grant numbers CA-77118, CA-801217, CA-84354, CA-115857 (for patient identification, enrollment and follow-up) to P. Yang and K12 CA090628 to A. Mansfield.]
Footnotes
Addendum
A. Tafur and A. Mansfield were responsible for the study conception and design; all authors were responsible for the acquisition of data, and analysis and interpretation of data. A. Mansfield and A. Tafur drafted the manuscript and A. Mansfield, A. Tafus and C. Wang critically revised the manuscript.
Disclosure:
A. Mansfield received honoraria from Celgene and Genetech for an educational activity and participation in an advisory board in 2014 and 2015 respectively, outside the submitted work. The other authors state that they have no conflict of interest.
REFERENCES
- 1.Petterson TM, Marks RS, Ashrani AA, Bailey KR, Heit JA. Risk of site-specific cancer in incident venous thromboembolism: a population-based study. Thrombosis research. 2015;135:472–8. doi: 10.1016/j.thromres.2014.12.013. 10.1016/j.thromres.2014.12.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Khorana AA, Dalal MR, Lin J, Connolly GC. Health care costs associated with venous thromboembolism in selected high-risk ambulatory patients with solid tumors undergoing chemotherapy in the United States. ClinicoEconomics and outcomes research : CEOR. 2013;5:101–8. doi: 10.2147/CEOR.S39964. 10.2147/CEOR.S39964. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Khorana AA, Francis CW, Culakova E, Kuderer NM, Lyman GH. Thromboembolism is a leading cause of death in cancer patients receiving outpatient chemotherapy. Journal of thrombosis and haemostasis : JTH. 2007;5:632–4. doi: 10.1111/j.1538-7836.2007.02374.x. 10.1111/j.1538-7836.2007.02374.x. [DOI] [PubMed] [Google Scholar]
- 4.Kourelis TV, Wysokinska EM, Wang Y, Yang P, Mansfield AS, Tafur AJ. Early venous thromboembolic events are associated with worse prognosis in patients with lung cancer. Lung Cancer. 2014;86:358–62. doi: 10.1016/j.lungcan.2014.10.003. 10.1016/j.lungcan.2014.10.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Phan M, John S, Casanegra AI, Rathbun S, Mansfield A, Stoner JA, Tafur AJ. Primary venous thromboembolism prophylaxis in patients with solid tumors: a meta-analysis. Journal of thrombosis and thrombolysis. 2014;38:241–9. doi: 10.1007/s11239-013-1014-9. 10.1007/s11239-013-1014-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Lyman GH, Khorana AA, Kuderer NM, Lee AY, Arcelus JI, Balaban EP, Clarke JM, Flowers CR, Francis CW, Gates LE, Kakkar AK, Key NS, Levine MN, Liebman HA, Tempero MA, Wong SL, Prestrud AA, Falanga A. American Society of Clinical Oncology Clinical P. Venous thromboembolism prophylaxis and treatment in patients with cancer: American Society of Clinical Oncology clinical practice guideline update. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2013;31:2189–204. doi: 10.1200/JCO.2013.49.1118. 10.1200/JCO.2013.49.1118. [DOI] [PubMed] [Google Scholar]
- 7.Khorana AA, Kuderer NM, Culakova E, Lyman GH, Francis CW. Development and validation of a predictive model for chemotherapy-associated thrombosis. Blood. 2008;111:4902–7. doi: 10.1182/blood-2007-10-116327. 10.1182/blood-2007-10-116327. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Agnelli G, George DJ, Kakkar AK, Fisher W, Lassen MR, Mismetti P, Mouret P, Chaudhari U, Lawson F, Turpie AG, Investigators S-O. Semuloparin for thromboprophylaxis in patients receiving chemotherapy for cancer. The New England journal of medicine. 2012;366:601–9. doi: 10.1056/NEJMoa1108898. 10.1056/NEJMoa1108898. [DOI] [PubMed] [Google Scholar]
- 9.George D, Agnelli G, Fisher W, Kakkar AK, Lassen MR, Mismetti P, Mouret P, Lawson F, Turpie AG. Venous Thromboembolism (VTE) Prevention with Semuloparin in Cancer Patients Initiating Chemotherapy: Benefit-Risk Assessment by VTE Risk in SAVE-ONCO; American Society of Hematology 53rd meeting; 2011. https://ash.confex.com/ash/2011/webprogram/Paper39639.html. [Google Scholar]
- 10.Goldstraw P, Crowley J, Chansky K, Giroux DJ, Groome PA, Rami-Porta R, Postmus PE, Rusch V, Sobin L, International Association for the Study of Lung Cancer International Staging C Participating I. The IASLC Lung Cancer Staging Project: proposals for the revision of the TNM stage groupings in the forthcoming (seventh) edition of the TNM Classification of malignant tumours. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer. 2007;2:706–14. doi: 10.1097/JTO.0b013e31812f3c1a. 10.1097/JTO.0b013e31812f3c1a. [DOI] [PubMed] [Google Scholar]
- 11.Pepe MS, Feng Z. Improving biomarker identification with better designs and reporting. Clinical chemistry. 2011;57:1093–5. doi: 10.1373/clinchem.2011.164657. 10.1373/clinchem.2011.164657. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Pepe MS, Etzioni R, Feng Z, Potter JD, Thompson ML, Thornquist M, Winget M, Yasui Y. Phases of biomarker development for early detection of cancer. Journal of the National Cancer Institute. 2001;93:1054–61. doi: 10.1093/jnci/93.14.1054. [DOI] [PubMed] [Google Scholar]
- 13.Flinterman LE, van Hylckama Vlieg A, Rosendaal FR, Cannegieter SC. Body height, mobility, and risk of first and recurrent venous thrombosis. Journal of thrombosis and haemostasis : JTH. 2015;13:548–54. doi: 10.1111/jth.12860. 10.1111/jth.12860. [DOI] [PubMed] [Google Scholar]
- 14.Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94:496–509. Doi 10.2307/2670170. [Google Scholar]
- 15.Ay C, Dunkler D, Marosi C, Chiriac AL, Vormittag R, Simanek R, Quehenberger P, Zielinski C, Pabinger I. Prediction of venous thromboembolism in cancer patients. Blood. 2010;116:5377–82. doi: 10.1182/blood-2010-02-270116. 10.1182/blood-2010-02-270116. [DOI] [PubMed] [Google Scholar]
- 16.Macbeth F, Noble S, Evans J, Ahmed S, Cohen D, Hood K, Knoyle D, Linnane S, Longo M, Moore B, Woll PJ, Appel W, Dickson J, Ferry D, Brammer C, Griffiths G. Randomized Phase III Trial of Standard Therapy Plus Low Molecular Weight Heparin in Patients With Lung Cancer: FRAGMATIC Trial. Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2016;34:488–94. doi: 10.1200/JCO.2015.64.0268. 10.1200/JCO.2015.64.0268. [DOI] [PubMed] [Google Scholar]
- 17.Mungo B, Zogg CK, Hooker CM, Yang SC, Battafarano RJ, Brock MV, Molena D. Does obesity affect the outcomes of pulmonary resections for lung cancer? A National Surgical Quality Improvement Program analysis. Surgery. 2015;157:792–800. doi: 10.1016/j.surg.2014.10.016. 10.1016/j.surg.2014.10.016. [DOI] [PubMed] [Google Scholar]
- 18.Agnelli G, Gussoni G, Bianchini C, Verso M, Mandala M, Cavanna L, Barni S, Labianca R, Buzzi F, Scambia G, Passalacqua R, Ricci S, Gasparini G, Lorusso V, Bonizzoni E, Tonato M, Investigators P Nadroparin for the prevention of thromboembolic events in ambulatory patients with metastatic or locally advanced solid cancer receiving chemotherapy: a randomised, placebo-controlled, double-blind study. The Lancet Oncology. 2009;10:943–9. doi: 10.1016/S1470-2045(09)70232-3. 10.1016/S1470-2045(09)70232-3. [DOI] [PubMed] [Google Scholar]
- 19.Sohal DP, Shrotriya S, Glass KT, Pelley RJ, McNamara MJ, Estfan B, Shapiro M, Wey J, Chalikonda S, Morris-Stiff G, Walsh RM, Khorana AA. Predicting early mortality in resectable pancreatic adenocarcinoma: A cohort study. Cancer. 2015;121:1779–84. doi: 10.1002/cncr.29298. 10.1002/cncr.29298. [DOI] [PubMed] [Google Scholar]
- 20.Ay C, Reitter E-M, Riedl J, Wagner O, Zielinski C, Pabinger I. A risk scoring model for cancer-associated venous thromboembolism is predictive for overall survival in patients with cancer. Journal of thrombosis and haemostasis : JTH. 2013;11:51. [Google Scholar]