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BP Variability is a Predictor
When I was undergoing induction therapy for multiple myeloma I wish I knew that BP variability is a predictor of chemotherapy-induced cardiotoxicity. At the time of my induction therapy, I had no idea that 5 of my chemo regimens were cardiotoxic and would probably cause chemotherapy-induced cardiomyopathy one day.
I was diagnosed with chemotherapy-induced cardiomyopathy 15 years after I underwent the cardiotoxic regimens that I mention in the post above.
While the doctor in the video linked below explains the basics of cardiotoxicity and the potential heart damage that different chemo regimens can do to the human heart, he doesn’t explain the evidence-based non-conventional therapies that can minimize or even prevent chemotherapy-induced cardiomyopathy.
What is cardiotoxicity? What is chemotherapy-induced cardiomyopathy?
The key issue then, the takeaway, is that because BP variability is a predictor of chemo-induced heart damage, cancer patients can identify possibly heart damage early in the induction process. This means that, hopefully, affected patients can undergo therapies, conventional or non-conventional, that can possibly prevent further heart damage from occurring.
David Emerson
- MM Survivor
- MM Cancer Coach
- Director PeopleBeatingCancer
Blood pressure variability as predictor of cancer therapy-related cardiovascular toxicity in patients with Multiple Myeloma
“Blood pressure (BP) variability (BPV) is an independent predictor of cardiovascular (CV) events. The role of BPV in defining risk of cancer therapy-related cardiovascular toxicity (CTR-CVT) is currently unknown.
The aims of this study were:
- (i) to evaluate BPV in a population of patients with Multiple Myeloma, undergoing proteasome inhibitors therapy;
- (ii) to assess the predictive value of BPV for CTR-CVT; (iii) to analyze clusters of subjects based on BPV.
One hundred twenty-four patients underwent a baseline evaluation, including
- Ambulatory Blood Pressure Monitoring (ABPM),
- PWV,
- and Echocardiography.
BPV was assessed through ABPM-based standard deviation (SD), weighted standard deviation (wSD), coefficient of variation (CoV), average real variability (ARV), and variability independent of the mean (VIM).
Individuals who developed CTR-CVT had a higher baseline BPV. Furthermore, night-time BPV was associated with CTR-CVT, independently of age, smoking, BP, diabetes, dyslipidemia, and kidney function (night-time systolic CoV: adjusted OR 1.09 [1.01–1.21]; night-time systolic VIM: adjusted OR 1.18 [1.01–1.39]).
Cut-offs for these BPV parameters were identified as predictors of CTR-CVT occurrence: 10.5 for night-time systolic CoV; 7.8 and 6.4 for systolic and diastolic night-time VIM. Clustering analysis identified subgroups of subjects characterized by the highest BPV, who had a greater prevalence of events, but no differences in other CV risk determinants.
Short-term BPV is an independent predictor of CTR-CVT. BPV may enhance the precision of risk stratification in cancer patients, enabling identification of individuals at higher risk who would not be recognized, if traditional prognostic indicators were the sole applied criteria.”
BLOOD PRESSURE VARIABILITY AS PREDICTOR OF CANCER THERAPY-RELATED CARDIOVASCULAR TOXICITY IN PATIENTS WITH MULTIPLE MYELOMA
“Results: The study population included 124 patients (50% female). During follow-up, CTR-CVT occurred in 70 subjects (56.5% of the total population), including both BP and CV events. Night-time BPV was associated to CTR-CVT, independently by BP, age, smoking, and comorbidities as diabetes and renal dysfunction (night-time systolic CoV: adjusted OR 1.11 [1.01-1.22]; night-time systolic VIM adjusted OR 1.17 [1.03-1.35]; night-time diastolic VIM adjusted OR 1.18 [1.01-1.40]).
Cut-off for these BPV parameters were identified as predictor of CTR-CVT occurrence: 10.5 for night-time systolic CoV (sensibility 73%, specificity 47%); 7.8 and 6.4 for systolic and diastolic night-time VIM (sensibility 85% for both; specificity 35% and 39%, respectively).
Clustering analysis identified a subgroup of subjects characterized by the highest BPV, who had a greater prevalence of events during follow-up, but no differences in other conventional CV risk factors, as BP, dyslipidaemia, diabetes, renal function, and smoking habit, as well as left ventricular mass and global longitudinal strain.
Conclusions: Short-term BPV is an independent predictor of CTR-CVT in patients with Multiple Myeloma undergoing therapy with Carfilzomib. The inclusion of these indexes improves CV risk prediction in these subjects and higher BPV is a distinctive feature predicting adverse events, on top of conventional CV risk factors.”
BP variability is a predictor