Beukenlaan 137
5616 VD Eindhoven
The Netherlands
+31 85064 55 82
info@clinlabint.com
PanGlobal Media is not responsible for any error or omission that might occur in the electronic display of product or company data.
Featured Articles
Diagnostic testing for Clostridium difficile: where to go from here?
Clostridium difficile causes serious life-threatening infections but this organism has a complex pathogenesis that makes differentiating true infection from asymptomatic carriage difficult. There are a number of diagnostic testing approaches that can be used alone or in multi-step algorithms. This review discusses the impact that the type of diagnostic test has on interpretation of clinically significant infection, initiation of treatment of C. difficile infection, and how future diagnostic testing may need to differentiate asymptomatic carriage from clinically significant disease.
by Dr Michelle J. Alfa
Clostridium difficile pathogenesis
Since the initial report by Bartlett et al. in 1978 [1] that C. difficile could cause infectious diarrhoea in patients who were treated with antibiotics (in particular clindamycin), there have been significant changes in the understanding of the pathogenesis of this organism as well as the approach to the diagnosis of the illness it causes. Initially, C. difficile was thought to be solely a hospital-acquired infection associated with a history of antibiotic consumption. Subsequently it became clear that humans can have toxigenic C. difficile present asymptomatically in their gastrointestinal tract and, unlike other enteric pathogens, the concept of ‘infectious dose’ does not really apply to this gastrointestinal pathogen. C. difficile infection (CDI) is a ‘two-hit’ process (Fig. 1). The first hit is ingestion of the metabolically inactive spore form which does not produce toxin, and the second hit is an imbalance of the gut microbiome (most often due to antibiotic therapy that eradicates gut normal flora without killing the spore or vegetative form of C. difficile). These two hits allow the ingested spore to germinate in the gut to the vegetative form which then replicates and produces Toxin A (enterotoxin) and Toxin B (cytotoxin). These toxins work synergistically to cause mucosal inflammation in the colon and diarrhoea (the small intestine is not damaged). Although the toxins do not appear to spread systemically, there is evidence that humoral antibodies against C. difficile Toxin A and B are protective.
In addition to exposure to spores in the healthcare environment or on the hands of caregivers, recent evidence implicates food products (beef, pork, fowl) as a source of C. difficile spores. This food reservoir may be the basis of community-acquired CDI (CA-CDI) as it is now recognized that up to 30% of all CDIs are acquired outside of healthcare facilities and, as discussed by Humphries et al. [2], patients with CA-CDI are more likely to have mild disease, shorter hospital stay and lower rates of mortality. Unlike other enteric vegetative bacterial pathogens in food products that are killed by adequate cooking, the spore form of C. difficile is not killed by cooking [3]. Consumption of C. difficile spores via food or iatrogenic exposure does not automatically lead to disease. Indeed up to 10–20% of healthy people and up to 70% of healthy neonates may harbour this toxigenic C. difficile in their gut but be asymptomatic [3, 4]. It is unknown if this represents transient passage of the ingested spores in the gut where the microbiome keeps C. difficile spores from germinating and replicating thereby preventing toxin production, or whether there can be asymptomatic colonization by toxigenic C. difficile at such low levels that there is no mucosal damage or diarrhoea. Guerrero et al. [5] reported that 12% of asymptomatic patients screened carried toxigenic C. difficile. Although the skin levels and environmental shedding from asymptomatic carriers was lower than from patients with CDI, it has been suggested [5] that asymptomatic carriers may still represent a significant reservoir for transmission within healthcare facilities.
The unique characteristics of C. difficile that include spore formation, asymptomatic carriage and ‘two-hit’ pathogenesis present challenges in terms of optimizing and interpreting diagnostic tests.
Diagnostic testing for toxigenic C. difficile
Over the past 20 years there has been a dramatic revolution in the approach to diagnostic testing for toxigenic C. difficile. Initially in the 1970s the diagnosis of C. difficile-associated diarrhoea was made by culture and subsequent testing of C. difficile isolates to determine if they were toxigenic or not [4, 6]. This was replaced by the cytopathic effect (CPE) assay in the late 1970s and early 1980s that detected biologically active Toxin B directly from the stool sample. Some still consider the CPE assay to be the most clinically relevant diagnostic test as it demonstrates there is sufficient biologically active toxin in stool to cause mucosal damage and diarrhoea. Because culture and CPE assays were labour intensive, costly, time consuming and required specialized expertise, antigen detection assays became the diagnostic test of choice early in the 1990s [4]. However, recent studies have documented that enzyme immunoassay (EIA) for Toxin A and B alone is insensitive and should not be used as a sole diagnostic test for CDI [2, 4, 6–10]. Some researchers advocate that toxigenic culture is the most sensitive diagnostic test [9]. Isolates must subsequently be tested to confirm they are toxigenic. Because toxigenic culture is too slow for clinical testing, multi-step algorithms using glutamate dehydrogenase (GD) antigen as a screen followed by CPE or nucleic acid amplification tests (NAATs) (Table 1) have been recommended [4, 6]. Within the past 5 years there has been a push towards using NAAT alone as the most rapid and sensitive diagnostic test for toxigenic C. difficile [4, 6, 8].
Longtin et al. [7] have recommended that diagnostic testing for C. difficile should be standardized because reportable rates of CDI are dramatically affected by the diagnostic test method or test algorithm utilized. They undertook a one year prospective study and reported that using NAAT alone instead of a multi-step algorithm based on GD antigen, Toxin A/B antigen and CPE assay resulted in a greater than 50% increase in CDI rate in their facility (8.9 cases by NAAT versus 5.8 cases by multi-step algorithm per 10,000 patient days). Their study was the first to report that for patients who were test positive by NAAT alone there was a 3% complication rate compared to the 39% complication rate for patients who were positive by both NAAT and their multi-step algorithm. The lack of standardization in diagnostic testing means the incidence rates reported will vary depending on the test method(s) used. The resultant increase in CDI incidence using NAAT tests compared to other testing algorithms has implications including; Medicare reimbursement penalties in the USA, financial penalties for increased CDI rates in England, target rates in Quebec, Canada.
Additional research is needed to clarify the clinical significance of NAAT positive tests when CPE and antigen tests are negative. As suggested by a variety of published reports [6–8, 10, 11], it may be wrong to assume that higher sensitivity makes for a better C. difficile diagnostic test. Leslie et al. [12] reported that quantitation of C. difficile copy number is reliable and they suggested this added information may help determine when therapy is warranted for NAAT positive tests. They reported that 30.6% of stools that were only positive by NAAT, and had no toxin detected by CPE or antigen testing had low C. difficile copy number/ml. Their data suggests that a large portion of NAAT positive samples fall into this category of ‘questionable’ clinical significance. Vancomycin treatment of asymptomatic C. difficile carriers has been shown to itself stimulate CDI and indeed the authors warned against antibiotic treatment for asymptomatic C. difficile carriers. It may be that detection by NAAT of low organism load represents spores (i.e. no toxin present) or may represent vegetative levels that do not require antibiotic therapy. Dionne et al. [10] reported good correlation between low levels of viable C. difficile and test positivity by NAAT only (i.e. negative by CPE and antigen detection). Furthermore, they were able to demonstrate a correlation between PCR cycle time (CT) and the level of viable C. difficile in the stool sample (Table 2).
Although many published manuscripts and reviews list sensitivity and specificity values, these are all dependent upon what is used as the ‘gold standard’. For C. difficile this is not a simplistic issue. It is clear that detection of toxigenic C. difficile by culture does not always indicate clinically significant disease.
Conclusions
As summarized in Table 3, there are a number of unresolved issues relating to diagnostic testing for C. difficile. For asymptomatic carriers of C. difficile who do not have diarrhoea, the concept of NAAT admission screening and contact precautions for those who test positive has yet to be determined to be beneficial in preventing the spread of CDI. For those patients with diarrhoea it is apparent that CDI rates will vary dramatically depending on the testing algorithm used. It is clear that NAAT used alone as a sole diagnostic test will overestimate CDI rates and could lead to unnecessary antibiotic therapy. The impact is substantive as about one-third of all NAAT positive results fall into this ‘grey area’ of doubtful clinical relevance (i.e. have no detectable toxin in the stool sample and/or are toxigenic culture negative).
In conclusion, a combination NAAT test that provides a quantitative assessment of the load of C. difficile in stool along with detection of C. difficile toxin genes appears to be the ideal combination of data in order to reliably determine which patients have clinically significant CDI and require treatment. However, prospective studies that assess clinical outcome based on this quantitative NAAT testing are needed to confirm that this diagnostic approach is optimal.
References
1. Bartlett JG, Chang TW, Gurwith M, Gorbach SL, Onderdonk AB. Antibiotic-associated pseudomembranous colitis due to toxin-producing clostridia. N Engl J Med. 1978; 298(10): 531–534.
2. Humphries RM, Uslan DZ, Rubin Z. Performance of Clostridium difficile toxin enzyme immunoassay and nucleic acid amplification tests stratified by patient disease severity. J Clin Microbiol. 2013; 51(3): 869–873.
3. Gupta A, Khanna S. Community-acquired infection: an increasing public health threat. Infect Drug Resist. 2014; 7: 63–72.
4. Tenover FC, Baron EJ, Peterson LR, Persing DH. Laboratory diagnosis of Clostridium difficile infection can molecular amplification methods move us out of uncertainty? J Mol Diagn. 2011; 13(6): 573–582.
5. Guerrero DM, Becker JC, Eckstein EC, Kundrapu S, Deshpande A, Sethi AK, et al. Asymptomatic carriage of toxigenic Clostridium difficile by hospitalized patients. J Hosp Infect. 2013; 85(2): 155–158.
6. Dubberke ER, Han Z, Bobo L, Hink T, Lawrence B, Copper S, et al. Impact of clinical symptoms on interpretation of diagnostic assays for Clostridium difficile infections. J Clin Microbiol. 2011; 49(8): 2887–2893.
7. Longtin Y, Trottier S, Brochu G, Paquet-Bolduc B, Garenc C, Loungnarath V, et al. Impact of the type of diagnostic assay on Clostridium difficile infection and complication rates in a mandatory reporting program. Clin Infect Dis. 2013; 56(1): 67–73.
8. Brecher SM, Novak-Weekley SM, Nagy E. Laboratory diagnosis of Clostridium difficile infections: there is light at the end of the colon. Clin Infect Dis. 2013; 57(8): 1175–1181.
9. Cohen SH, Gerding DN, Johnson S, Kelly CP, Loo VG, McDonald LC, et al. Clinical practice guidelines for Clostridium difficile infection in adults: 2010 update by the society for healthcare epidemiology of America (SHEA) and the infectious diseases society of America (IDSA). Infect Control Hosp Epidemiol. 2010; 31(5): 431–455.
10. Dionne LL, Raymond F, Corbeil J, Longtin J, Gervais P, Longtin Y. Correlation between Clostridium difficile bacterial load, commercial real-time PCR cycle thresholds, and results of diagnostic tests based on enzyme immunoassay and cell culture cytotoxicity assay. J Clin Microbiol. 2013; 51(11): 3624–3630.
11. Su WY, Mercer J, Van Hal SJ, Maley M. Clostridium difficile testing: have we got it right? J Clin Microbiol. 2013; 51(1): 377–378.
12. Leslie JL, Cohen SH, Solnick JV, Polage CR. Role of fecal Clostridium difficile load in discrepancies between toxin tests and PCR: is quantitation the next step in C. difficile testing? Eur J Clin Microbiol Infect Dis. 2012; 31(12): 3295–3299.
The author
Michelle J. Alfa, PhD
Boniface Research Centre, Dept. of Medical Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
E-mail: malfa@dsmanitboa.ca
Viral hepatitis, the silent epidemic
Globally as many people (1.5 million) die each year from viral hepatitis as from HIV/AIDS, but whereas the latter viral disease attracts government and international action and funding, the former is comparatively neglected. It was for this reason that the WHO initiated World Hepatitis Day four years ago, to be observed on the 28th July each year, and the lack of awareness about the repercussions of viral hepatitis was reflected in this year’s theme of ‘Hepatitis: think again’. So far five hepatitis viruses have been identified, though Hepatitis D is only found as a co-infection with B. Whilst the acute infections that food- and water-borne Hepatitis A and E cause are not insignificant in terms of their incidence, morbidity and mortality, it is Hepatitis B and C (HBV and HCV), that are generating a global public health crisis.
These two viral infections have major characteristics in common with HIV/AIDS. The acute infection, acquired by exposure to infectious blood and other body fluids as well as by sexual and vertical transmission, is frequently asymptomatic in the case of HCV. Acute infections can be followed by a period of clinical latency and thus the unwitting transmission of the virus to others. Though such chronic infections with HBV are very uncommon in healthy adults, they occur in over half of young children infected; between 75% – 85% of people infected with HCV develop a chronic infection. After years or even several decades of chronic, asymptomatic infection, cirrhosis of the liver and hepatocellular carcinoma can result. The WHO estimates that there are around 780,000 deaths from acute and chronic HBV infection, and more than 350,000 from chronic HCV infection annually. Even more alarming is that currently 500 million people are chronically infected with either HBV or HCV.
As is the case with HIV/AIDS, avoiding exposure to infectious blood and semen and diagnostic testing of asymptomatic people can help to contain the global viral hepatitis epidemic. However, now the pertinent characteristics of the disease have been elucidated, it should be far more feasible to control viral hepatitis than HIV/AIDS, a disease for which there is no vaccine and no drugs that actually eradicate the virus. There is a highly effective vaccine for HBV, though approved drugs help prevent serious
liver damage but don’t eliminate the virus. Drugs are now available that can eradicate the HCV virus, and clinical trials are currently testing
a vaccine for chronically infected people.
“Hepatitis: think again”. With appropriate education and adequate national and international funding, this looming global health crisis could be averted.
Tumour markers for the diagnosis of mucinous ovarian cancer
The aim of this study was to determine the accuracy of CEA, CA 15.3, CA 19.9 and CA 125 for diagnosis of mucinous ovarian cancer (MOC). We studied 94 women with mucinous ovarian tumour, 82 were NOT MOC (68 mucinous ovarian cystadenomas and 14 mucinous borderline ovarian tumour) and 12 were MOC. All MOC patients were in FIGO stage I or II. No statistically significant differences were found between MOC and NOT MOC patients according to CEA and CA 15.3 (P>0.05). AUC values were 0.862 (P=0.0002) and 0.829 (P=0.0021) for CA 19.9 and CA 125 respectively. In conclusion, preoperative CA 19.9 and CA 125 levels showed high diagnosis efficacy to predict whether a mucinous ovarian tumour is benign or malignant.
by Dr J. D. Santotoribio, A. Garcia-de la Torre, C. Cañavate-Solano, F. Arce-Matute, M. J. Sanchez-del Pino and S. Perez-Ramos
Introduction
Ovarian cancer is the fifth leading cause of cancer-related death in women in developed countries and has one of the highest ratios of incidence to death [1]. Epithelial ovarian cancer is a heterogeneous disease with a heterogeneous distribution pattern [2]. Epithelial ovarian cancer set by the World Health Organization recognizes eight histological tumour subtypes: serous, mucinous, endometrioid, clear cell, transitional cell, squamous cell, mixed epithelial and undifferentiated [3]. Mucinous ovarian cancer (MOC) is an epithelial ovarian cancer that contains cysts and glands lined by mucin-rich cells and historically accounted for approximately 11.6% of all primary epithelial ovarian carcinomas [4]. MOC should be considered separate from the other epithelial ovarian cancers as metastatic primary disease and recurrent mucinous cancers have a substantially worse prognosis than other epithelial ovarian cancers [5]. Tumour markers are biochemical substances found in the blood which may be measured for the diagnosis of cancer. The major challenge of developing a screening test using serum tumour markers, is that it must be highly specific (because of the low prevalence of ovarian cancer) in order to avoid detection of numerous false positives [6]. The most common tumour markers in clinical chemistry are carcinoembryonic antigen (CEA), cancer antigen 15.3 (CA 15.3), cancer antigen 19.9 (CA 19.9) and cancer antigen 125 (CA 125). CEA and CA 15.3 have been found at elevated levels in patients with epithelial ovarian cancer [7–9]. Preoperative elevated CA 19.9 levels are related to a higher probability of MOC [8, 10]. A diagnostic approach based on the use of CA 125 has been suggested for the early diagnosis of ovarian cancer, although premenopausal women may have higher serum CA 125 levels than in postmenopausal women [11–13]. Also, in mucinous borderline ovarian tumours have found a significant relation with elevated CA 125 [14, 15]. Another tumour marker for diagnosis of ovarian cancer, serum human epididymis protein 4 (HE4), has lowest concentrations in mucinous tumours and displays no difference in serum concentration between benign or malignant mucinous ovarian tumours [12, 13].
The aim of this study was to determine the accuracy of CEA, CA 15.3, CA 19.9 and CA 125 for diagnosis of MOC in patients with mucinous ovarian tumors.
Materials and methods
Women with mucinous ovarian tumours diagnosed between 2004 and 2012 were included in the study. We excluded patients with other tumours that could elevate the tumour markers. Before biopsy and after obtaining an informed consent, blood specimens were drawn by venipuncture in gel separator serum tubes and centrifuged at 4000 rpm for 4 min. The following variables were analysed: CEA, CA 15.3, CA 19.9 and CA 125. We measured the serum concentrations of the tumour markers by electrochemiluminescence immunoassay (ECLIA) in MODULAR E-170 (ROCHE DIAGNOSTIC®). The reference range values provided by our laboratory are: CEA (0–3.4 ng/mL), CA 15.3 (0–30 U/mL), CA 19.9 (0–37 U/mL) and CA 125 (0–35 U/mL). After surgery, histology and stage were determined according to the International Federation of Gynecologists and Obstetricians (FIGO) classification. Patients were classified into two groups according to the diagnosis of ovarian biopsy: NOT MOC (mucinous ovarian cystadenomas and mucinous ovarian borderline tumour) and MOC. For all statistical comparisons a value of P<0.05 was considered significant. The accuracy of serum tumour markers was determined using receiver operating characteristic (ROC) techniques by analysing the area under the ROC curve (AUC). The optimal cut-off value was considered with higher than 95% specificity. Statistical analysis was performed using the software MEDCALC®.
Results
We enrolled 94 women aged between 15 and 80 years old (median age was 43). Eighty-two patients (87.2 %) were NOT MOC (68 mucinous ovarian cystadenomas and 14 mucinous ovarian borderline tumours) and 12 patients (12.8 %) were MOC. Thirty-two patients were postmenopausal and 62 patients were premenopausal. All MOC patients were in FIGO I or II stages.
Descriptive statistics of serum tumour markers in MOC and NOT MOC patients are shown in Table 1. No statistically significant differences were found between MOC and NOT MOC patients according to CEA and CA 15.3 (P>0.05). The frequency of abnormal serum levels CA 19.9 and CA 125 in MOC and NOT MOC patients are shown in Table 2. AUC, optimal cut-off value, sensitivity and specificity of ROC curves for diagnosis of MOC using CA 19.9 and CA 125 are displayed in Table 3.
No statistically significant differences were found between premenopausal and postmenopausal women for CEA, CA 15.3, CA 19.9 and CA 125. Also, these tumour markers were not statistically significant for the diagnosis of mucinous borderline ovarian tumours (P>0.05).
Discussion
In the literature, CEA has been noted to be elevated in almost one third of all ovarian carcinomas. CEA is much more likely to be elevated in mucinous ovarian carcinomas than in non-mucinous ovarian carcinomas [5, 7, 8]. CA 15.3 has been found to be elevated levels in patients with advanced epithelial ovarian cancer [8, 9]. However, in this study, CEA and CA 15.3 were not useful to differentiate benign from malignant mucinous ovarian tumours.
In the recent paper of the guidelines on the recognition and initial management of ovarian cancer from the National Institute for Health and Clinical Excellence (NICE) stated that general practitioners should measure serum CA 125 in primary care in women with symptoms that suggest ovarian cancer [11]. Also, a diagnostic approach based on the use of CA 125 in association with ultrasonography has been suggested for the early diagnosis of ovarian cancer [11, 12]. The major drawback of using CA 125 as a screening strategy is that up to 20% of ovarian cancers do not express the antigen, and also that abnormal serum levels CA 125 may be found in patients with benign ovarian tumours [12, 13]. Recently, another tumour marker for ovarian cancer has been proposed, serum human epididymis protein 4 (HE4), frequently overexpressed in ovarian cancers, especially in serous and endometrioid histology [6, 12, 13]. However, HE4 has lowest concentrations in mucinous tumours and shows no difference in serum concentrations between benign or malignant mucinous ovarian tumours [12, 13]. Serum CA 19.9 presents low efficiency for the diagnosis of serous ovarian cancer, but preoperative elevated CA 19.9 levels could be related to a higher probability of MOC [8, 10]. In this paper, CA 125 false positive results (abnormal serum levels) were found in 31.7 % of NOT MOC patients and false negative (normal serum levels) in 33.3 % of MOC patients. CA 19.9 false positive results were found in 19.5 % of NOT MOC group and false negative in 16.6 % of MOC group. All MOC patients had abnormal serum CA 19.9 and/or CA 125 levels, and 60.98 % NOT MOC patients presented normal CA 19.9 and CA 125 (Table 2). Both tumour markers showed similar sensitivity (50%) in MOC diagnosis and slightly higher specificity with CA 19.9 (97.6%) than with CA 125 (95.1%) (Table 3).
In some studies [12, 13], significantly higher serum CA 125 levels were found in premenopausal women than in postmenopausal women; in our case this is not significant (P>0.05). In other study, up to 61% of women with borderline ovarian tumours had elevated CA 125 [14]. In mucinous borderline ovarian tumours with papilla formation, others authors found a significant relation between elevated CA 125 [15]. In our patients, CA 125 and CA 19.9 were not statistically significantly different (P>0.05) for the diagnosis of mucinous borderline ovarian tumours.
In conclusion, preoperative CA 19.9 and CA 125 levels showed high diagnosis efficacy to predict whether a mucinous ovarian tumour is benign or malignant.
References
1. emal A, Siegel R, Xu J, Ward E. Cancer statistics. CA Cancer J Clin. 2010; 60: 277–300.
2. Sung PL, Chang YH, Chao KC, Chuang CM. Task Force on Systematic Review and Meta-analysis of Ovarian Cancer. Global distribution pattern of histological subtypes of epithelial ovarian cancer: a database analysis and systematic review. Gynecol Oncol. 2014; 133: 147–54.
3. Lee KR, Tavassoli FA, Prat J, et al. WHO histological classification of tumours of the ovary. In: Pathology and genetics of tumours of the breast and female genital organs. Edited by Tavassoli FA, Devilee P. IARC Press 2003; 113–161.
4. Nolen B, Marrangoni A, Velikokhatnaya L, et al. A serum based analysis of ovarian epithelial tumourigenesis. Gynecol Oncol. 2009; 112: 47–54.
5. Frumovitz M, Schmeler KM, Malpica A, et al. Unmasking the complexities of mucinous ovarian carcinoma. Gynecol Oncol. 2010; 117: 491–496.
6. Husseinzadeh N. Status of tumour markers in epithelial ovarian cancer has there been any progress? A review. Gynecol Oncol. 2011; 120: 152–157.
7. Tholander B, Taube A, Lindgren A, et al. Pretreatment serum levels of CA-125, carcinoembryonic antigen, tissue polypeptide antigen, and placental alkaline phosphatase in patients with ovarian carcinoma: influence of histological type, grade of differentiation, and clinical stage of disease. Gynecol Oncol. 1990; 39: 26–33.
8. Terzic M, Dotlic J, Likic I, et al. Diagnostic value of serum tumour markers evaluation for adnexal masses. Cent Eur J Med. 2014; 9: 210–216.
9. Gemer O, Oustinov N, Gdalevich M, et al. Pretreatment CA 15-3 levels do not predict disease-free survival in patients with advanced epithelial ovarian cancer. Tumori. 2013; 99: 257–260.
10. Kelly PJ, Archbold P, Price JH, et al. Serum CA 19.9 levels are commonly elevated in primary ovarian mucinous tumours but cannot be used to predict the histological subtype. J Clin Pathol. 2010; 63: 169–173.
11. Sturgeon CM, Duffy MJ, Walker G. The National Institute for Health and Clinical Excellence (NICE) guidelines for early detection of ovarian cancer: the pivotal role of the clinical laboratory. Ann Clin Biochem. 2011; 48: 295–299.
12. Molina R, Escudero JM, Augé JM, et al. HE4 a novel tumour marker for ovarian cancer: comparison with CA 125 and ROMA algorithm in patients with gynaecological diseases. Tumour Biol. 2011; 32: 1087–1095.
13. Escudero JM, Auge JM, Filella X, et al. Comparison of serum human epididymis protein 4 with cancer antigen 125 as a tumour marker in patients with malignant and nonmalignant diseases. Clin Chem. 2011; 57: 1534–1544.
14. Morotti M, Menada MV, Gillott DJ, et al. The preoperative diagnosis of borderline ovarian tumours: a review of current literature. Arch Gynecol Obstet. 2012; 285: 1103–1112.
15. Alanbay I, Aktürk E, Coksuer H, et al. Comparison of tumour markers and clinicopathological features in serous and mucinous borderline ovarian tumours. Eur J Gynaecol Oncol. 2012; 33: 25–30.
The authors
J. D. Santotoribio1,2,*, A. Garcia-de la Torre1,2, C. Cañavate-Solano1,2, F. Arce-Matute1, M. J. Sanchez-del Pino2, S. Perez-Ramos1,2
1Clinical Biochemistry Laboratory, Puerto Real University Hospital, Cadiz, Spain
2Dept. of Biomedicine, Biotechnology and Public Health, University of Cadiz, Cadiz, Spain
*Corresponding author
E-mail: jdsantotoribioc@gmail.com