Prospective Assessment of Clinical Risk Factors and Biomarkers of Hypercoagulability for the Identification of Newly diagnosed chemotherapy Naïve Patients with Multiple Myeloma at Risk for Cancer-associated Thrombosis. The Observational ROADMAP-CAT-MM Study

2018 ◽  
Vol 164 ◽  
pp. S235
Author(s):  
D. Fotiou ◽  
L. Papageorgiou ◽  
S. Salta ◽  
E. Terpos ◽  
J. Fareed ◽  
...  
2009 ◽  
Vol 27 (29) ◽  
pp. 4839-4847 ◽  
Author(s):  
Alok A. Khorana ◽  
Gregory C. Connolly

PurposePatients with cancer are increasingly at risk for venous thromboembolism (VTE). Rates of VTE, however, vary markedly among patients with cancer.DesignThis review focuses on recent data derived from population-based, hospital-based, and outpatient cohort studies of patients with cancer that have identified multiple clinical risk factors as well as candidate laboratory biomarkers predictive of VTE.ResultsClinical risk factors for cancer-associated VTE include primary tumor site, stage, initial period after diagnosis, presence and number of comorbidities, and treatment modalities including systemic chemotherapy, antiangiogenic therapy, and hospitalization. Candidate predictive biomarkers include elevated platelet or leukocyte counts, tissue factor, soluble P-selectin, and D-dimer. A recently validated risk model, incorporating some of these factors, can help differentiate patients at high or low risk for developing VTE while receiving chemotherapy.ConclusionIdentifying patients with cancer who are most at risk for VTE is essential to better target thromboprophylaxis, with the eventual goal of reducing the burden as well as the consequences of VTE for patients with cancer.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 4520-4520
Author(s):  
Ilicia L. Shugarman ◽  
Randy A Brown ◽  
Christopher R Cogle ◽  
John W Hiemenz ◽  
W. Stratford May ◽  
...  

With the new treatments for multiple myeloma (MM), increasing numbers of patients fail to mobilize sufficient peripheral blood stem cells (PBSC) for autologous stem cell transplant (ASCT). Multiple studies have identified clinical and laboratory factors, such as age, number of lines of chemotherapy, radiation exposure, bone marrow involvement, and low PLT count as risks for poor mobilization. However, there are fewer studies that analyze only the effect of multiple clinical risk factors on mobilization outcomes. We retrospectively analyzed 259 MM patients who underwent first apheresis after GCSF mobilization between December 2000 and December 2012. Clinical risk factors analyzed include age, number of lines of chemotherapy, number of cycles of chemotherapy, number of doses of cyclophosphamide, number of doses of lenalidomide, and prior external beam radiation. The standard dose of GCSF was 10 mcg/kg/day, however the exact dose for a significant number of patients was not known. Patients were assessed as to whether optimal (≥8x106 CD34+ cells/kg) or minimal (≥4x106 CD34+ cells/kg) number of stem cells for two ASCTs were collected. The median age of the entire cohort was 59.7 years (27.9-76.0). Overall 10.8% and 32.6% failed to collect the minimal and optimal number of stem cells after one round of apheresis. Of the twenty patients who underwent a second round of apheresis, 9 (45%) collected minimal and 7 (35%) collected optimal total number of stem cells, with an overall failure rate of 4.6% and 29.8%, respectively. The effect of the number of clinical risk factors on the mobilization failure during first apheresis is summarized in Table 1. For each additional clinical risk factor, the likelihood of collecting the minimal and optimal number of CD34+ cells is reduced by 34% (CI=0.484-0.893, p=0.0072) and 32% (CI=0.538–0.860, p=0.0013) respectively. On univariate analysis, all risk factors were analyzed as continuous variables, except for prior radiation which was analyzed as a categorical variable. Prior lenalidomide exposure (odds ratio=0.502, CI=0.297–0.845, p=0.0096), and prior radiation therapy (odds ratio=0.502, CI=0.293–0.861, p=0.0123) had the greatest negative predictive value. Of the 38 patients who were exposed to lenalomide (median 4 cycles; range 1-24 cycles), 13% and 42% failed to collect minimal and optimal number of stem cells in the first apheresis cycle, respectively. An association was seen between number of days required to collect target number of stem cells and number of risk factors (p≤0.001). Median number of days required to collect target number of stem cells for 0, 1 or 2+ clinical risk factors was 2, 2, and 4 days, respectively. When the effect of clinical risk factors were analyzed according to number of CD34+ cells/kg collected on each day of apheresis, statistically significant differences in collection efficiency were seen on the first 3 days of apheresis (Figure 1). In summary, clinical characteristics of patients with MM can potentially be used to predict mobilization failure. The presence of 2 or greater clinical risk factors adversely affect the ability to successfully collect the target stem cell dose. These risk factors may help in identifying high-risk MM patients who may benefit from alternative mobilization regimens that can be tested in prospective clinical trials.Number of Clinical Risk Factors012+N1128561% Patients not collecting optimal # of cells on 1st apheresis cycle23.231.850.895% CI15.8-32.122.1-42.833.7-63.9p-value0.19710.0003% Patients not collecting minimal # of cells on 1st apheresis cycle5.411.818.095% CI2.0-11.35.8-20.69.4-30.0p-value0.11950.0096Median number of days of collection224Range1-81-91-10p-value0.4233<0.0001 Disclosures: No relevant conflicts of interest to declare.


2014 ◽  
Vol 38 (2) ◽  
pp. 188-193 ◽  
Author(s):  
Junling Zhuang ◽  
Yi Da ◽  
Hui Li ◽  
Bing Han ◽  
Xia Wan ◽  
...  

2019 ◽  
Vol 156 (1) ◽  
pp. 43-45 ◽  
Author(s):  
Andrew T. Kunzmann ◽  
Marisa Cañadas Garre ◽  
Aaron P. Thrift ◽  
Úna C. McMenamin ◽  
Brian T. Johnston ◽  
...  

2021 ◽  
Vol 11 (11) ◽  
Author(s):  
Mirian Brink ◽  
Kaz Groen ◽  
Pieter Sonneveld ◽  
Monique C. Minnema ◽  
Annemiek Broijl ◽  
...  

AbstractIdentification of risk factors for early mortality (EM) in multiple myeloma (MM) patients may contribute to different therapeutic approaches in patients at risk for EM. This population-based study aimed to assess trends in EM and risk factors for EM among MM patients diagnosed in the Netherlands. All MM patients, newly diagnosed between 1989 and 2018, were identified in the Netherlands Cancer Registry. Patients were categorized into three calendar periods (1989–1998, 1999–2008, 2009–2018) and into five age groups (≤65, 66–70, 71–75, 76–80, >80 years). EM was defined as death by any cause ≤180 days post-diagnosis. We included 28,328 MM patients (median age 70 years; 55% males). EM decreased from 22% for patients diagnosed in 1989–1998 to 13% for patients diagnosed in 2009–2018 (P < 0.01) and this decrease was observed among all age groups. Exact causes of death could not be elucidated. Besides patient’s age, we found that features related to a more aggressive disease presentation, and patient characteristics reflecting patients’ physical condition were predictive of EM. In summary, EM decreased from 1999 onwards. Nevertheless, EM remains high, especially for patients aged >70 years. Therefore, novel strategies should be explored to improve the outcome of patients at risk for EM.


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