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As the appearance of circulating tumour cells in the peripheral blood of breast cancer patients is linked to a worse prognosis for overall survival and treatment efficiency, their detection and characterization will have a high impact on cancer therapy, opening roads to a more personalized treatment.
by Dr U. Andergassen, Dr A. C. Kölbl, Prof. K. Friese and Prof. U. Jeschke
Circulating tumour cells
Already in 1869 the occurrence of cancer cells in the peripheral blood of a metastatic cancer patient was described by Thomas Ashworth. Nowadays it is well known, that cells dissolve from primary epithelial tumours such as breast, lung, colon or prostate cancer, enter circulation and travel via the blood stream or lymphatic system throughout the whole body. If these cells [termed circulating tumour cells (CTCs)] leave circulation, they can settle at other sites in the body and are then considered to be the main reason for the generation of remote metastasis. Their appearance is linked to a poorer outcome of cancer therapy and to a worse prognosis for overall survival. Therefore, the detection of CTCs in peripheral blood [and of disseminated tumour cells (DTCs) in bone marrow] was already included into the international tumour staging systems.
Unfortunately the detection of CTCs is still a technical challenge, as the number of tumour cells in the blood stream is rather small (1 in 106–7 blood cells). To date, there is only one FDA-approved system for CTC detection, at least in the metastatic situation. This is the Cell Search® system (Veridex LLC.), which is based on immunomagnetic enrichment and simultaneous staining of tumour cells of epithelial surface markers, the cytokeratins. The huge disadvantage of this system is that it is rather expensive and, therefore, not yet routinely used in the clinic.
Real-time PCR in cancer cell detection
Another promising approach for CTC detection could be a real-time PCR-based method. The principle of this methodology is that breast-cancer CTCs are derived from an epithelial tumour, and, therefore, express a panel of epithelial cell genes. The surrounding blood cells in contrast are of mesenchymal origin, showing different gene expression profiles. Thus, it can be assumed that tumour cells are present in a given blood sample if the expression of epithelial genes is higher than in a negative control sample.
Real-time PCR measures gene expression levels by detecting an increase of fluorescence due to the incorporation of fluorescent reporter molecules into the newly synthesized DNA molecules during the PCR reaction. If a gene is highly expressed, a lot of mRNA of this gene is present, meaning plenty target for PCR reaction is available and thus influencing the fluorescence level measured at the end of each amplification cycle. The time point when fluorescence reaches a certain threshold is called the Ct-value, and this is the basis of the calculation of relative gene expression values by the 2-∆∆Ct-method [1]. In brief: the average Ct-value of a gene of interest is related to the average Ct-value of a reference gene. The resulting value is called the ΔCt-value. In the next step, this ΔCt-value is set in reference to the ΔCt-value of the same gene in the reference sample, rendering the so called ΔΔCt-value. The formula 2–ΔΔCt is then used to calculate relative quantification (RQ) values. RQ values >1 show an upregulation of the gene of interest, values <1 mean that the gene is downregulated.
Spiking experiments
The first step towards a real time PCR based quantitative cancer diagnosis is to create calibration curves for the used marker genes to evaluate the number of cancer cells exhibited at a certain level of gene expression in a blood sample. Therefore, blood samples of healthy donors, to which a certain number of cells from a breast-cancer cell line were added, were used to create standard curves. For this evaluation different breast-cancer cell lines were used (Cama-1, MCF-7, MDA-MB231 and ZR-75-1), and real-time PCR was carried out for Cytokeratin 8, 18 and 19 as marker genes [2, 3]. Cancer cells were added in rising numbers and calibration curves could be drawn [Fig. 1], showing an increase in gene expression level from 10 cells added to a blood sample upwards, meaning that even a small number of cancer cells in the blood (resembling the ‘real’ conditions, with 1 CTC per106–7 surrounding blood cells) can be detected by this methodology.
PCR marker genes for CTC detection
As CTCs in the blood are rare, PCR marker genes have to be selected as accurately as possible. The first choice are the Cytokeratin (CK) genes 8, 18 and 19, as they are also used in the routinely applicated APAAP-staining, which is a histochemical detection method for CTCs. The cytokeratin family members are characteristic epithelial cell markers and only weakly expressed in blood cells, rendering them potentially useful for PCR-based detection of CTCs.
Three other genes (BCSP, MGL, Her2) were selected and used in an approach to detect differences in gene expression between normal individuals and adjuvant and metastatic breast-cancer patients [4]. Mammaglobin (MGL) is a gene which is only expressed in the adult mammary gland and is known to be upregulated in breast cancer [5]. Breast cancer specific protein (BCSP) is highly expressed in advanced infiltrating breast cancer and is a marker for recurrence of the disease and formation of metastases [6], and c-erbB2 (Her2) was used, because it is over-expressed in 20% of breast cancers and is also responsible for the aggressiveness of the tumour [7].
These markers were comparatively analysed in blood samples withdrawn from adjuvant and metastatic breast-cancer patients during surgery. The gene expression levels of adjuvant as well as metastatic breast-cancer patients were normalized to levels in blood samples from 20 healthy donors, considered as a negative control group. Differences in gene expression between the three sample groups were detected [Fig. 2] and it was attempted to find a signature of marker genes for CTCs in breast cancer by real-time PCR.
From the experiments, it could be concluded that cytokeratin genes seem to be the most promising markers for the detection of CTCs from peripheral blood of breast-cancer patients with reverse-transcription real-time PCR. The most suitable marker of the cytokeratin array is apparently CK8, rendering most expression values >1.
MGL, BCSP, and Her2 mRNA show few expression values >1 as well in adjuvant as in metastatic patients. Altogether, higher amplitudes for these three genes were detected in the adjuvant setting. CTCs can be detected from peripheral blood by real-time-PCR, using the cytokeratin markers, especially cytokeratin 8.
In contrast to these findings are the results published by Obermayr et al. 2010 [8], who found an overexpression of MGL/hMAM in 39% of the examined advanced breast cancer cases. But they also conclude that using more marker genes for CTC detection results in a higher percentage of detected cancer cases. The same findings were obtained by [9], who also used a real-time PCR-based approach for CTC detection. They used CK19, SCGB2A2, MUC1, EPCAM, BIRC5 and Her-2 as marker genes and found a high sensitivity and specificity (56.3% and 100% respectively).
Additionally CK20 was identified as a promising marker gene [10] and seems to be correlated with the aggressiveness of the tumour. To further improve the detection of CTCs by real-time-PCR, more marker genes need to be tested; promising candidates are, for example, MMP13 [11], UBE2Q2 [12],
Nectin-4 [13], and ALDH [14].
Future directions for cancer therapy
Real-time PCR-based techniques were already used for solid tumour profiling and are considered to be objective, robust and cost-effective molecular techniques that could be used in routine cancer diagnosis. In future, a real-time PCR assay for the detection of circulating tumour cells from peripheral blood could find its way into modern medicine. This would be advantageous for the patient by limiting the number of invasive procedures, such as biopsies or bone marrow aspirations, that have to be undertaken to produce samples for analysis.
Furthermore by implication of more marker genes a characterization of tumour cells could be pursued, which already gives hints towards a cancer prognosis, as for example Bölke et al. described, that the expression of certain genes is correlated to advanced breast cancer stages [15]. A better knowledge of cancer properties in turn will help to apply a more personalized therapy, side effects can be reduced and treatment efficiency will strongly increase.
References
1. Livak KJ, Schmittgen TD. Methods 2001; 25(4): 402–408.
2. Zebisch M, Kolbl AC, Schindlbeck C, Neugebauer J, Heublein S, Ilmer M, Rack B, Friese K, Jeschke U, Andergassen U. Anticancer Res 2012; 32(12): 5387–5391.
3. Zebisch M, Kölbl AC, Andergassen U, Hutter S, Neugebauer J, Engelstädter V, Günthner-Biller M, Jeschke U, Friese K. Biomedical reports; accepted for publication 2012.
4. Andergassen U, Hofmann S, Kolbl AC, Schindlbeck C, Neugebauer J, Hutter S, Engelstadter V, Ilmer M, Friese K, Jeschke U. Int J Mol Sci 2013; 14(1): 1093–1104.
5. Fleming TP, Watson MA. Ann N Y Acad Sci 2000; 923: 78–89.
6. Wu K, Weng Z, Tao Q, Lin G, et al. Cancer Epidemiol Biomarkers Prev 2003; 12(9): 920–925.
7. Kim YS, Konoplev SN, Montemurro F, Hoy E, Smith TL, et al. Clin Cancer Res 2001; 7(12):4008–4012.
8. Obermayr E, Sanchez-Cabo F, Tea MK, Singer CF, Krainer M, et al. BMC Cancer 2010; 10: 666.
9. de Albuquerque A, Kaul S, Breier G, Krabisch P, Fersis N. Breast Care (Basel) 2012; 7(1): 7–12.
10. Tunca B, Egeli U, Cecener G, Tezcan G, Gokgoz S, Tasdelen I, et al. Tumori 2012; 98(2): 243–251.
11. Chang HJ, Yang MJ, Yang YH, Hou MF, Hsueh EJ, Lin SR. Oncol Rep 2009; 22(5): 1119–1127.
12. Nikseresht M, Seghatoleslam A, Monabati A, et al. Cancer Genet Cytogenet 2010; 197(2): 101–106.
13. Fabre-Lafay S, Garrido-Urbani S, Reymond N, et al. J Biol Chem 2005; 280(20): 19543–19550.
14. Dontu G. Breast Cancer Res 2008; 10(5): 110.
15. Bolke E, Orth K, Gerber PA, Lammering G, Mota R, et al. Eur J Med Res 2009; 14(8): 359–363.
The authors
Ulrich Andergassen* MD, Alexandra C. Kölbl PhD, Klaus Friese MD, and Udo Jeschke PhD
Klinik und Poliklinik für Frauenheilkunde und Geburtshilfe, Ludwig Maximilian University of Munich, Munich, Germany
*Corresponding author
ulrich.andergassen@med.uni-muenchen.de
Leaders from the medical diagnostics, laboratory medicine, and healthcare fields convened in Houston, Texas, July 28 – August 1 for the AACC annual meeting, the world’s largest diagnostics conference and expo. Over 17,000 attendees took part in the event and the exhibit totalled more than 625 companies. A selection of research papers presented in Houston are summarized below.
New biomarkers for prostate cancer
Dimitra Georganopoulou, PhD, Ohmx Corporation, presented results of a pilot study to find a new biomarker for prostate cancer aggressiveness. The researchers measured the enzyme activity of prostate-specific antigen (PSA), termed the “aPSA”, in patient specimens that had been removed by radical prostatectomy. They wanted to determine if this activity level could be a clue to how aggressive the cancer was. The team found that there was a significant negative correlation between prostate cancer progression and the aPSA in prostatic fluid. Patients with the least amount of aPSA (PSA activity) had the most aggressive prostate cancer. Tests for an “aggressiveness biomarker” would provide critical information for making decisions about when clinical treatment should occur or when it could be postponed. Many men might be able to avoid radical treatments if their cancer was known to be non-aggressive. Likewise, men whose cancer was too aggressive to employ the “active surveillance” or “watchful waiting” approach would have more information to help them make meaningful personal decisions with the help of their doctors about what level of treatment was right for them. The findings from this study could lead to the development of a new tool to use along with existing screening tests.
PSA Enzymatic activity: A new biomarker for assessing prostate cancer aggressiveness.
Dimitra Georganopoulou, PhD, OHMX Corporation, Evanston, Ill., U.S.A.
Diagnosing cystic fibrosis at the point of care
Xuan Mu from Peking Union Medical College presented test results from cystic fibrosis patients using an exciting new point-of-care method. Microfluidics and colour changes within a Band-Aid type of adhesive strip on the skin allow the new device to rapidly, accurately, and quantitatively diagnose cystic fibrosis in a small amount of sweat. Detecting sweat chloride has been the gold standard in diagnosing cystic fibrosis for more than 50 years. The new test detects increased chloride in sweat using a colour change in paper on an adhesive strip when a very small amount of sweat is absorbed. The intensity of changed colour is recorded with a cell phone camera, and is then measured against a colour model. Cystic fibrosis in an inherited disease of the body’s mucus glands. Technically a rare disease, the incidence of cystic fibrosis varies around the world and by ethnic group. Different mutations in the CFTR gene cause the severity and symptoms of CF to vary considerably. Respiratory and digestive systems are affected, as well as sweat glands and reproductive systems. The new point-of-care test device can distinguish healthy people from cystic fibrosis samples and conveniently integrates the many separate steps of current sweat chloride tests whose results take several hours to obtain. Treatment advances have increased the life expectancy of cystic fibrosis patients over the past several decades from the mid-teens in the 1970s to more than 36 years today in the U.S. An early diagnosis and a comprehensive treatment plan can improve both survival and quality of life of patients. This new method demonstrates a fast and cost-effective opportunity in diagnosing cystic fibrosis.
On-site colorimetric detection of sweat chloride ion for diagnosing cystic fibrosis.
Xuan Mu, Peking Union Medical College, Beijing, China
Determining the safety of olanzapine for schizophrenia and bipolar disorder
AACC member Werner Steimer from Munich, Germany presented the results of research showing that study patients who carried a specific genetic variation in an antipsychotic-metabolizing enzyme developed significantly higher serum concentrations of the drug olanzapine. The increased drug concentrations were still noteworthy even when researchers accounted for differences in the patient’s age, sex, weight, and other medications that they used. This is the first study to demonstrate that this polymorphism influences serum levels of olanzapine, and the study is extremely timely in the context of the recent FDA safety alert on the injectable form of olanzapine, an “atypical” or second generation antipsychotic medication. Under investigation are two unexplained deaths of patients who received an intramuscular injection of Zyprexa Relprevv (olanzapine pamoate) and showed very high blood levels of the drug, although they had received appropriate doses. They died 3-4 days after injection. Olanzapine is approved by the U.S. FDA for treating schizophrenia and bipolar disorder in adults and children older than 13, and is one of the most widely prescribed of the atypical antipsychotics. Olanzapine is available in tablet, injectable, and long-acting “depot” formulations. Long acting medications can be more tolerable to some patients and help them adhere to treatment. Olanzapine is metabolized in the liver by specific cytochrome P450 enzymes. Some individuals have genetic variations – polymorphisms – of cytochrome enzymes. These can impact the way that drugs are broken down and distributed throughout the body and sometimes even the strength or effectiveness of treatment.
The CYP1A2*1D Polymorphism has a significant impact on Olanzapine serum concentrations.
Werner Steimer, MD, Klinikum Rechts der Isar – Technische Universität München, Munich, Germany.
Sepsis is a complex syndrome associated with significant morbidity and mortality. If detected and treated early, septic patients have better prognoses. Unfortunately, identification of sepsis is challenging because its pathophysiology is complex and its clinical signs and symptoms overlap with other inflammatory diseases. This review discusses emerging biomarker panels and their ability to predict sepsis in critically ill patients.
by Dr A. Woodworth and Dr J. Colon-Franco
Sepsis and SIRS: International definitions
Definitions of sepsis and related conditions date back to the 1991 consensus conference held by the American College of Chest Physicians and the Society of Critical Care Medicine [1].
This consensus group introduced the term SIRS to describe the systemic inflammatory response syndrome, a normal response to infection and non-infectious insults like trauma, pancreatitis, and burns [Figure 1]. In SIRS two or more of the following clinical signs manifest: abnormal body temperature (fever or hypothermia), tachypnea, tachycardia and abnormal white blood cell count (leukocytosis or leukopenia).
The consensus group defined sepsis as the presence of SIRS along with a documented infection. Left untreated, septic patients develop severe sepsis, characterized by organ dysfunction, and ultimately septic shock, characterized by organ failure, hypotension and decreased peripheral perfusion. Revision of these definitions in 2001, added ‘suspected infection’ to the classification of sepsis to address numerous clinical cases where microorganisms cannot be confirmed.
For over 20 years, these definitions have provided uniformity in clinical disease recognition and better characterized patient populations for sepsis research. Although recognition of SIRS is relatively straightforward, identification of patients with sepsis among those with SIRS remains challenging. This is due, in part, to overlapping clinical signs and symptoms between SIRS and sepsis as well as inherent difficulty in confirming infectious causes of SIRS.
Sepsis and SIRS: Pathobiology and related syndromes
Sepsis pathobiology is complex and not well characterized [Figure 2] [1]. Historical models describing an overactive proinflammatory response to infection likely oversimplify the process. Sepsis experts now support two distinct pathogenesis models for the progression of sepsis. The sequential response model describes an initial proinflammatory response to a pathogen, SIRS, followed by a compensatory anti-inflammatory response syndrome (CARS). In the second model, known as the mixed antagonist response syndrome, SIRS and CARS occur simultaneously and achieve homeostasis. Severe sepsis and septic shock are associated with an imbalance in the SIRS/CARS equilibrium. Although recent research supports the second model [2], larger studies exploring the underlying pathobiology, including expression of pro- and anti-inflammatory molecules throughout the course of sepsis pathogenesis are needed.
Sepsis diagnosis
Rapid diagnosis and treatment of sepsis reduces mortality. The ‘gold standard’ for sepsis diagnosis is identification of an infectious microorganism in patients with SIRS. Traditionally, pathogens in blood, urine or other body fluids were detected in the laboratory by culturing. Unfortunately, cultures have limited utility because some pathogens are slow growing and contamination is common, leading to a high number of false negative and positive results. Despite their disadvantages, identification of the infecting agent as well as its antibiotic susceptibility and resistance patterns remains crucial to administer or adjust antimicrobial treatment. Direct identification of a pathogen through molecular and proteomic-based approaches may help overcome these disadvantages [3].
Because of its non-specific clinical symptoms and the limited utility of bacterial cultures, researchers have looked to biomarkers to diagnose sepsis. Currently, the diagnostic utility of sepsis biomarkers is limited to confirming, ruling out sepsis or stratifying patients based on disease severity. Lactate, C-reactive protein (CRP) and procalcitonin (PCT) assist in the work-up of patients with suspected sepsis. Lactate, the end product of anaerobic glycolysis, is increased in septic shock and other conditions as a result of excessive energy demand, tissue hypoxia, and/or impaired metabolic pathways.
The Surviving Sepsis Campaign, an international collaboration developed to improve the management, diagnosis, and treatment and reduce mortality rates of sepsis, advocates measuring blood lactate within 6 h of presentation in patients with suspected sepsis [1]. A lactate concentration >4 mmol/L (36 mg/dL) is associated with increased morbidity and mortality and is used to guide sepsis resuscitation protocols. Lactate concentrations increase with severity of sepsis and are most useful for diagnosing septic shock, but lack diagnostic strength to discriminate early sepsis from SIRS.
Expression of proinflammatory molecules is markedly up-regulated in early sepsis. CRP and PCT expression is stimulated by proinflammatory cytokines. CRP is an acute phase reactant that is up-regulated in inflammatory processes, and is not specific for sepsis. PCT, the precursor of calcitonin in thyroidal C-cells, is systemically produced in non-thyroidal tissue in response to inflammation and infection. Compared to CRP, PCT more accurately distinguishes SIRS from sepsis [1, 4]. In critically ill adults, the diagnostic strength of PCT to distinguish sepsis from SIRS is low [1, 4]. This may be due to the fact that like CRP, PCT is overexpressed in non-infectious inflammatory states like surgery or trauma. Unlike CRP, PCT concentrations correlate with sepsis severity. Both CRP and PCT can predict prognosis and response to therapy in septic patients. PCT is also useful in ruling out bacterial infections and is used in algorithms guiding antimicrobial therapy in critically-ill patients [4]. However, because of its questionable diagnostic utility, PCT testing is not universally used in clinical practice.
Thousands of studies have investigated the clinical and diagnostic utility of hundreds of sepsis biomarkers. A recent review of relevant clinical and experimental studies identified 178 proposed sepsis biomarkers [4]. Besides PCT and CRP, 34 others were investigated as diagnostic markers for sepsis. None had sufficient diagnostic strength to differentiate septic patients from those with non-infectious SIRS.
Multiple biomarker panels for sepsis diagnosis
As our understanding of the underlying mechanisms of sepsis evolved, it became evident that a single biomarker could not identify all patients with this heterogeneous syndrome. Instead, a panel of biomarkers, consisting of molecules secreted in the blood throughout the disease process, may better predict sepsis among patients with systemic inflammation [3].
Recent studies [Table 1] explored the utility of novel multimarker panels to predict sepsis. In a prospective cohort study of 151 emergency department (ED) patients with SIRS, both panels of 3 and 6 biomarkers showed superior diagnostic utility for detection of bacterial infection compared to any single biomarker [Table 1; Study #1] [5]. In a separate cohort of 342 ED patients with SIRS, adding 1 to 3 biomarkers and/or clinical parameters did not improve upon PCT alone to predict bacteremia [Table 1; #2] [6]. In the latter study, only patients with documented positive blood cultures were included, excluding possible infection in other sites or fluids and patients with false negative cultures.
In a retrospective pilot study at our institution, 10 inflammatory biomarkers, chosen because of their expression pattern during SIRS and/or CARS, were measured in 63 critically-ill patients with SIRS [Table 1; #3]. Panels of 2 to 6 inflammatory biomarkers measured in multiplex were better able to identify sepsis among patients with SIRS compared to single markers. Because of the small sample size, a 2-marker panel was most predictive of sepsis. PCT and CRP showed limited diagnostic utility alone or in combination with other biomarkers [7]. In a second retrospective cohort study we evaluated the diagnostic utility of 5 inflammatory biomarkers up-regulated in SIRS and/or CARS in 169 ICU patients with SIRS [Table 1; #4]. The 5-biomarker panel outperformed any single biomarker to predict sepsis on the day that patients developed SIRS [8]. Studies are ongoing to validate these findings in a larger population and to compare these results with the diagnostic performance of PCT.
A sepsis risk score, generated from results of multiple biomarkers, may allow easy adoption of these panels into clinical practice [3, 9]. A study evaluating the plasma concentrations of 5 proinflammatory molecules demonstrated that, compared to individual markers, a sepsis score consisting of at least 2 biomarkers elevated above their respective cut-offs better discriminated between SIRS and sepsis in ICU patients [Table 1; #5] [10]. Gibot and colleagues investigated the concentration of three biomarkers in 300 patients consecutively admitted into the ICU [Table 1; #6] [9]. A bioscore of 0, 1, 2 or 3 was assigned based on the number of positive biomarkers (above pre-defined cut-off values). The bioscore surpassed the diagnostic strength of any of the individual biomarker results for the prediction of sepsis. This model was validated in a separate cohort of 228 patients presenting with clinical signs of sepsis. In these studies, the sepsis score strategy was practical with superior diagnostic utility.
Conclusions
Early identification and treatment of septic patients reduces mortality, however, signs and symptoms of early sepsis are similar to non-infectious SIRS. To date, no single biomarker has ample diagnostic strength to identify septic patients among a critically-ill population. A panel of biomarkers may better distinguish patients with sepsis from those with non-infectious SIRS. Most findings are from preliminary studies with small patient cohorts and require additional validation studies. These should be conducted in larger, multicentre populations with distinct validation cohorts. Rapid, automated, multiplexing platforms and/or point-of-care technologies may be necessary to obtain timely results for these multimarker sepsis panels. Combining biomarkers into equations or sepsis-scores that yield an interpretable and meaningful result is paramount for their clinical adoption.
In conclusion, using combinations of biomarkers to predict sepsis is an attractive strategy that may improve real time assessments and reduce morbidity and mortality in septic patients.
References
1. Faix JD. Established and novel biomarkers of sepsis. Biomark Med 2011; 5(2): 117–130.
2. Osuchowski MF, et al. Sepsis chronically in MARS: systemic cytokine responses are always mixed regardless of the outcome, magnitude, or phase of sepsis. J Immunol 2012; 189(9): 4648–56.
3. Casserly B, Read R, Levy MM. Multimarker panels in sepsis. Crit Care Clin 2011; 27(2): 391–405.
4. Pierrakos C, Vincent JL. Sepsis biomarkers: a review. Crit Care 2010; 14(1): R15.
5. Kofoed K, et al. Use of plasma C-reactive protein, procalcitonin, neutrophils, macrophage migration inhibitory factor, soluble urokinase-type plasminogen activator receptor, and soluble triggering receptor expressed on myeloid cells-1 in combination to diagnose infections: a prospective study. Crit Care 2007; 11(2): R38.
6. Tromp M, et al. Serial and panel analyses of biomarkers do not improve the prediction of bacteremia compared to one procalcitonin measurement. J Infect 2012; 65(4): 292–301.
7. Pyle AL, et al. Multiplex cytokine analysis for the differentiation of SIRS and sepsis. Am J Clin Pathol 2010; 134: 509.
8. Pyle AL, et al. A multi-marker approach to differentiate sepsis from SIRS. Am J Clin Pathol 2011; 136: 468–469.
9. Gibot S, et al. Combination biomarkers to diagnose sepsis in the critically ill patient. Am J Respir Crit Care Med 2012; 186(1): 65–71.
10. Selberg O, et al. Discrimination of sepsis and systemic inflammatory response syndrome by determination of circulating plasma concentrations of procalcitonin, protein complement 3a, and interleukin-6. Crit Care Med 2000; 28(8): 2793–2798.
The authors
Alison Woodworth, PhD, DABCC, FACB
Assistant Professor, Pathology, Microbiology and Immunology
Director, Esoteric Chemistry
Vanderbilt University Medical Center
Nashville, TN, USA
Jessica M. Colón-Franco, PhD
Clinical Chemistry Fellow
Department of Pathology, Microbiology and Immunology
Vanderbilt University Medical Center
Nashville, TN, USA
E-mail:
Alison.Woodworth@Vanderbilt.Edu
Cardiovascular disease (CVD) is still widely considered as a middle-aged man’s disease and this is clearly a misconception. In actual fact, CVD is the number one cause of death for women worldwide. Also, compared with men, women have a number of additional risk factors that are specific to them and should not be ignored by medical professionals. Laboratory testing has a key role to play in the diagnosis and follow up of women with CVD. CLI talked to Jean Onofrio, Senior Director, Global Assay Marketing, Siemens Healthcare Diagnostics, about this important health issue for women.
Q.What impact does cardiovascular disease have on women?
Cardiovascular disease, or CVD, is a significant health concern for women. In fact, it’s the number one killer of women globally, [1] and according to the World Health Organization (WHO), accounts for one-third of deaths in women.
CVD also is the main cause of death for older women. Women generally develop CVD about 10 years later in life than men, likely due to the protective, anti-oxidant effects of estrogen prior to menopause.
Unfortunately, the misperception that CVD is a middle-aged man’s disease still persists. Understanding CVD’s global impact on women is one positive step toward battling the disease.
Q. What are the risk factors for CVD in women? How do these compare to risk factors in men?
While many CVD risk factors, such as age, family history and high blood pressure, are similar in both genders, there are some, including diabetes, tobacco use and high triglyceride levels, that put women at higher risk. Other risk factors, like obesity and depression, are more prevalent in women. There are also some risk factors unique to women, including pregnancy complications, oral contraceptive use, hormone replacement therapy and polycystic ovary syndrome. It’s important for women to understand their CVD risk factors and discuss their concerns with their physician.
Q. How does the mortality rate of women with CVD compare to the mortality rate of CVD in men?
While the mortality rate is high for older women, a heart attack can occur at any age. For younger women, heart attacks are actually more deadly than for men. According to the American Heart Association (AHA), among adults aged 45-62, women are twice as likely as men to die within the first year after a heart attack.
Also, more than twice as many women will develop heart failure within five years of surviving a heart attack compared to men, and three times more women than men will suffer a stroke after surviving a heart attack.
Q. What are some of the challenges associated with diagnosing CVD in women?
Women having a heart attack commonly present with symptoms other than chest pain, which makes diagnosis challenging. Rather, women often experience such less common symptoms as fatigue, indigestion, appetite loss and
“heart flutters.”
Even though these symptoms may not be severe, they may still lead to deadly consequences. Unfortunately, many women, and often clinicians, disregard their symptoms, attributing them to other non-life-threatening conditions.
Adding to this challenge, women with CVD aren’t as likely as men to receive aggressive diagnosis and treatment. Consider that women receive only about 34 percent of interventional treatments, with and witout the placements of stents.
Q. What role does laboratory testing play in the diagnosis and management of women with CVD? What about biomarkers?
CVD is largely preventable, and simple laboratory tests can help assess a person’s risk.
Laboratory professionals play an increasingly important role in providing access to both traditional and novel cardiac biomarkers that are available throughout the disease continuum. Also, whether conducted in the central lab or at the point-of-care, cardiac tests, such as high-sensitivity troponin, are key diagnosis tools.
By leveraging the appropriate use of laboratory diagnostic testing, clinicians can help enhance the assessment, diagnosis and follow-up care for women with CVD.
Reference
1.http://gamapserver.who.int/gho/interactive_charts/women_and_health/causes_death/ chart.html; accessed 11/27/12
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