Abstract
Cancer remains a leading cause of mortality and morbidity worldwide. In addition to organ failure, the most frequent reasons for admission of cancer patients to intensive care units (ICU) are: infections and sepsis. As critically ill, the complexity of the health situation of cancer patients renders the standard antimicrobial regimen more complex and even inadequate which results in increased mortality rates. This is due to pathophysiological changes in the volume of distribution, increased clearance, as well as to organ dysfunction. While in the former cases a decrease in drug efficacy is observed, the hallmark of the latter one is overdosing leading to increased toxicity at the expense of efficacy. Furthermore, an additional risk factor is the potential drug-drug interaction between antibiotics and antineoplastic agents. Therefore, therapeutic drug monitoring (TDM) is a necessity to improve the clinical outcome of antimicrobial therapy in cancer patients. To be applied in routine analysis the method used for TDM should be cheap, fast and highly accurate/sensitive. Furthermore, as ICU patients are treated with a cocktail of antibiotics the method has to cover the simultaneous analysis of antibiotics used as a first/second line of treatment. The aim of the current review is to briefly survey the pitfalls in the current antimicrobial therapy and the central role of TDM in dose adjustment and drug-drug interaction’s evaluation. A major section is dedicated to summarize the currently published analytical methods and to shed light on the difficulties and potential problems that can be encountered during method development.
Introduction
According to the World Health Organization (WHO) the number of cancer related deaths reached 8.2 million in 2012. By 2025 this ailment is expected to affect 22 million individuals worldwide. A large body of evidence shows that increased risk of mortality and morbidity of critically ill/immunocompromised cancer patients is associated with their high susceptibility for infection such as severe pneumonia [1], [2], urinary tract infection [2], and blood stream infection [3] to name a few. Even though inadequacy of the antimicrobial therapy recommended for critically ill patients in intensive care units (ICU) is well known, the dramatic failure reported for cancer patients is alarming. The high percentage of infection-induced deaths in cancer patients is extremely high [4] and can increase even to 100%, depending on the strength of infection [5]. Poulikakos et al. show that during the period of 2013–2014 none of the critically ill cancer patients admitted to ICU due to H1N1 infection survived to discharge. Even after treatment with oseltamivir, all patients died from respiratory tract infection and multiple organs failure [5]. Recent studies show that the dosing regimen of two β-lactam antibiotics (cefepime and piperacillin), prescribed for febrile neutropenic patients with hematological malignancies, requires adjustment [6], [7] especially in the presence of organ dysfunction [8]. The need for dose adjustment is mainly due to the fact that the pathophysiological changes encountered in ICU patients substantially affect the pharmacokinetic profile of a drug predisposing the patients to toxic or sub-therapeutic concentrations, when standard doses are applied. In the latter condition an increase in the risk of acquiring bacterial resistance is also of concern [3], [9], [10]. This is alarming especially in cancer patients with neutropenia who are at higher risk for severe sepsis and, therefore, for poor clinical outcome. In addition to failure in the antibiotic therapy, another factor such as the prevalence of drug-drug interaction among antibiotics and antineoplastic agents could also exacerbate the failure/toxicity of the antimicrobial therapy in critically ill cancer patients [11]. Collectively, as the pathophysiological changes observed in critically ill patients differ widely inter- and intra-individually and due to the potential occurrence of drug-drug interaction, the establishment of specific guidelines to be used by the clinicians is unlikely to be successful [12], [13], [14]. Consequently, by tailoring the antimicrobial therapy and monitoring antibiotic-antineoplastic interaction, therapeutic drug monitoring (TDM) would serve as an invaluable tool to increase the efficacy and safe therapeutic use of both classes of drugs in critically ill/immunocompromised patients [15]. To be applied in routine analysis the method(s) used for TDM has to be fast, accurate and cost effective. Nowadays, liquid chromatography tandem mass spectrometry (LC-MS/MS) is the method of choice due to its accuracy and specificity along with the short turnover of analysis it offers. To date several reviews have been published focusing on the importance of TDM in improving antimicrobial treatment in critically ill patients, yet, to our knowledge none has tackled its relevance with respect to cancer patients and drug-drug interaction. In addition, no other reviews summarized the current LC-MS/MS methods developed for the simultaneous determination of different classes of antibiotics used as a first and second line of treatments in ICU. Therefore, this review will discuss briefly the drawbacks of the current antimicrobial therapy with specific emphasis on the importance of TDM in dose adjustment and in the study of antibiotic-antineoplastic drug interaction. As the focus of this review is to optimize the antimicrobial therapy of critically ill cancer patients, we will delineate only the analytical methods used for antibiotics determination. We will also shed the light on the main points that should be taken into account while developing a new method for the simultaneous analysis of the different classes of antibiotics used in ICU.
Current antibiotic therapy in ICU patients
The antimicrobial therapy of infection in ICU patients often relies on the use of the β-lactam class of antibiotics (carbapenems, penicillins, cephalosporins and monobactams) as well as other classes/antibiotics such as fluoroquinolones, sulfamide, oxalizidione and tigecyclin. Every treatment regimen aims to attain the pharmacokinetic/pharmacodynamics (PK/PD) target: maintain a proper concentration to induce the desired effects. Depending on the class of the antibiotics the PD kill characteristic can be (1) time-dependent (i.e.: β-lactams, carbapenems, linezolid), (2) concentration-dependent (i.e.: fluoroquinolones, daptomycin), and (3) concentration-dependent with time-dependence (i.e.: tygecyclin, linezolid, fluoroquinolones, aminoglycosides) [16], [17]. For time dependent antibiotics such as β-lactams the antibacterial activity is related to the time for which their unbound plasma concentration is maintained above the minimum inhibitory concentration (MIC) during a dosing interval (fT>MIC) [18], [19]. For several β-lactam antibiotics the PK/PD targets ranges from 40% to 70% of the dosing interval (40% fT>MIC to 70% fT>MIC) [18], [19]. On the other hand, for fluoroquinolones which exhibit concentration-dependent killing behavior [20], the best predictor of bacterial killing is the 24h AUC0−24 h/MIC (area under the concentration–time curve/MIC) while the peak plasma concentration Cmax/MIC is important to prevent the emergence of bacterial resistance [10]. Data based on clinical trials suggests that AUC0−24 h/MIC of >100 and <250 yield bacterial killing at slow rate (7 days), whereas AUC0−24 h/MIC of >250 ensure rapid bactericidal action (24 h) of fluoroquinolones for both Gram-negative and Gram-positive bacteria [20]. To avoid resistance of Gram-negative pathogens to fluoroquinolones the Cmax/MIC ratio should be >10–12 [20], [21].
Impact of pathophysiological changes on the antimicrobial therapy
The current antibiotic dosing regimen is based on studies performed with healthy volunteers or non-critically ill patients. Yet, the dramatic pathophysiological changes such as alterations in drug’s clearance and protein binding, volume of distribution (Vd) and acid–base balance, which change drug’s distribution confronted in ICU patients affect significantly the pharmacokinetic (PK) profile of the antibiotics used [22]. Furthermore, patients, presenting dysfunction in vital organs such as kidney and liver that represent the major routes for drug elimination, are at increased risk of the prompt onset of toxic drug concentration [12], [23]. On the other hand, patients with augmented renal clearance [24] or prescribed with continuous renal therapy suffer from decreased levels of antibiotics necessary to achieve a positive clinical outcome [25]. It is evident that different antibiotics are differently affected by the pathophysiological changes encountered in ICU patients. While hydrophilic antibiotics such as β-lactams are mostly affected by the pathophysiological changes in Vd and creatinine clearance [16], lipophilic antibiotics such as fluoroquinolones and tigecyclins have, nonetheless, lesser Vd alterations but may develop altered drug clearance [16], [17]. Several studies published so far support the idea that using the conventional dosage regimens recommended for patients with minor infections is not adequate for critically ill patients with severe infections. Compelling evidence demonstrates that the dosing recommendation of β-lactam antibiotics is inadequate in critically ill patients [19] and that the poor clinical outcome observed to date is related to poor antibiotics exposure [13], [18], [19], [26], [27], [28]. In an empirical study published in 2014 by De Waele et al. [19] data analysis from 68 ICU across 10 countries shows that around 20% of critically ill patients did not reach the most conservative β-lactams PK/PD target (50% fT>MIC), and 40% of them did not reach the 100% fT>MIC, which was independently associated with increased creatinine clearance. Furthermore, other studies indicate the large variations in the levels of the different classes of antibiotics used in ICU: cefepime [29], meropenem [30], piperacillin [14], linezolid [31], [32], [33], sulfamethoxazole/trimethoprim [34], fluconazole [13], [35], flucloxacillin [36], and ciprofloxacin [9], [10], [37]. In addition to the extensive inter-individual variation, intra-individual variation was observed for piperacillin [14] and linezolid [33].
Besides the documented poor exposure of antibiotics in ICU, emerging evidence supports the correlation of increased levels of β-lactams with increased toxicities such as increased occurrence of neurological deterioration (tazobactam and meropemen) [38], and seizure (cefepime) in critically ill patients [38], [39]. Collectively, the current knowledge proves the need for dose adjustment (amount and duration) in order to achieve a positive clinical outcome in critically ill patients. Even though all of the aforementioned studies were performed in critically ill non-cancer patients, similar results are anticipated due to the similar pathophysiological changes encountered in cancer patients as with other critically ill patients. Furthermore, convincing evidence shows that increased morbidity and mortality of cancer patients infected with resistant bacteria are more likely to occur following receipt of inadequate initial empirical antibiotic treatment [40].
Requirement of TDM to study antibiotic-antineoplastic interaction
Concomitant administration of a wide range of medications along with antineoplastic agents, characterized by their narrow therapeutic index and high level of inter-individual variability, to cancer patients leads to drug-drug interactions [11], [41], which account for about 4% of the reported cancer death [42]. The interaction can be manifested at (1) the pharmacokinetic level, by affecting the absorption, distribution, metabolism, elimination (ADME) of the drug itself or a combination of drugs, and (2) the pharmacodynamics level where the combination result in synergistic, antagonistic or additive effects [11]. Even though the use of antineoplastic agents is generally discontinued if the patients show local signs of infection and develops fever, some antineoplastic agents are not stopped and are co-administered with the prescribed antibiotics. Consequently, the knowledge of possible interaction between antibiotic and antineoplastic agents may be valuable [43]. The drawbacks of combination treatments between antibiotic and anticancer compounds have been documented back to as early as 1967 whereby an antagonism between benzylpenicillin (penicillin G) and the antineoplastic agent actinomycin D was confirmed [44]. Recently, toxicities resulting from a combination therapy of antibiotic and antineoplastic agents have been also documented [45]. Most of the reports are on the effect of the co-administration of antibiotics along with methotrexate (MTX), an anti-folate agent effective against different types of tumors such as lymphoma, osteosarcoma and bladder [45], [46], [47]. The observed toxicity was not limited to the combination of MTX with one class of antibiotics but covered different classes such as fluoroquinolones, β-lactams (i.e.: penicillin and cephalosporin), and sulfonamide. For instance, a life threatening toxicity was observed in a patient receiving ciprofloxacin, a fluoroquinolone, and a high dose of MTX to treat non-Hodgkin lymphomas [45]. The toxicity was due to a prolonged persistence of MTX in the plasma of the patient, probably due to a decrease in its renal elimination [45]. Delay in MTX elimination has been also documented in children concomitantly receiving ciprofloxacin [46]. Competition in renal clearance between MTX and penicillin antibiotics has been also reported three decades ago whereby the simultaneous presence of MTX and phenoxymethylpenicillin (penicillin V) resulted in transient toxicity in a case study of a patient with prostate cancer [47]. Other antibiotics such as amoxicillin, piperacillin, oxacillin and pristinamycin have similarly resulted in delayed clearance of MTX [48], [49]. Blockage of the proximal renal organic anion transporters OAT1 and OAT3 by antimicrobial agents was suggested as the reason for the decreased renal excretion and increased toxicity of MTX [45], [50]. However, along with a decrease in its clearance an additional mechanism has been observed when MTX was combined with trimethoprim (TMP)/sulfamethoxazole (SMZ) whereby an increase in MTX free unbound levels, through displacement from plasma proteins, was observed in children treated for leukemia [51]. As TMP is excreted by the organic cation system and not the organic anion system, the observed decrease in MTX clearance can be due to the inhibition of the latter one by the presence of SMZ [51], [52]. Interestingly, in opposition to the aforementioned antibiotics that enhanced MTX induced toxicities, TMP enhanced MTX anti-folate effect [48]. This is possibly due to the fact that TMP itself is an anti-folate; hence, it can act synergistically with MTX [53]. Drug-drug interaction has been also documented when nilotinib, used to treat chronic myeloid leukemia, was combined with antiretroviral drugs (ritonavir and efavirenz) [54]. The authors recommended TDM to achieve the desired dose and avoid toxic effects when the drugs are co-administered [54]. To date all the studies comments on the anticancer related toxicities associated with the concomitant presence of antibiotics but none evaluated the presence of anticancer drugs on the PK/PD of antibiotics which remains an interesting field of research that merits further investigation. Finally, TDM is not only important to adjust the dose of antimicrobial therapy and the anticancer therapy [15] but such monitoring will also help in identifying and avoiding drug potential interactions.
Overview of published analytical methods optimized for therapeutic drug monitoring
Current knowledge highlights the large variation in the levels of different classes of antibiotics prescribed to ICU patients. As these patients are usually prescribed with a cocktail of β-lactams and other classes of antibiotics, therefore, there is an increasing interest in providing a convenient method that enables the simultaneous analysis of the different antibiotics to assist quick decision in dose adjustment. A suitable method should be straightforward, with short turnover, and cost effective. Immunoassays are usually an attractive choice as they do not require special expertise, equipment or significant resources. Yet, immunoassays which have provided such advantages for antibiotics as aminoglycosides, do not exist for β-lactams and attempts for the establishment of such techniques have been difficult [6], [55]. Therefore, with the current limitations the use of immunoassays for antibiotics’ TDM is not considered as a priority for further development and efforts have been directed to explore other alternatives such as the use of chromatographic techniques. Consequently, liquid-chromatography (LC) coupled to UV [28], [56], [57], [58], [59], chemiluminescence (CL) [60], electrochemical (EC) [61], and mass spectrometry (MS) [62], [63], have been widely/successfully used for the detection of β-lactams. Although as compared to mass spectrometry less sophisticated analysis is performed with the use of the other conventional detectors, the speed and sensitivity of the former one surpass those offered by the latter ones (UV, CL, EC). The current interest focuses on LC-MS/MS [60], [64], [65], [66], [67], [68], [69], [70], [71], [72], [73], [74]. This is not surprising as it is well acknowledged that LC-MS/MS has the power of combining the sensitivity of tandem MS and the selectivity of chromatography thus improving the accuracy of quantitating low drug concentrations from different matrices. In many cases the use of LC-MS/MS offers an increase in the sensitivity by several orders of magnitude. For instance, reported lower limit of detection of some β-lactams achieved with LC-UV or LC-EC detectors is 5 mg/L [28], [61], while it reached 10–50 times lower levels (0.1–0.5mg/L) when LC-MS/MS is used [64], [74]. As in the case of critically ill patients very low levels can be anticipated methods that offer higher sensitivity are preferred. Furthermore, the analysis time with conventional detectors is usually lengthier from 10 to 22 min [28], [57] which makes them, in terms of the fast delivery of the results, less attractive for routine analysis when compared to LC-MS/MS which can offer analysis time of less than 5 min. There is no doubt that conventional methods are less expensive and can be also suitable for TDM; nevertheless, careful consideration should be made when availability, costs, speed and accuracy come into the play. Even though it is assumed that the implementation of LC-MS requires extremely sophisticated infrastructure, i.e. highly qualified trained personnel and expensive equipment; yet, in comparison to earlier eras the costs for mass spectrometry machines dropped significantly, used machines are readily available on the market and training of personnel is doable. Nowadays, the number of hospitals incorporating LC-MS in routine analysis is increasing. This is for the reason that the promising reward obtained in terms of fast delivery of results, faster success in patients treatment along with a decrease in the costs of medications and stay of patients in the hospital pay off for what a hospital would invest in the implementation of LC-MS in routine analysis.
LC-MS/MS for antibiotics therapeutic monitoring what shall we know?
Although different analytical methods have been developed for the quantification of individual antibiotics, in the last 5 years several methods have been published for the simultaneous analysis of subsets of antibiotics usually given to critically ill patients [64], [65], [66], [67], [68], [69], [70], [71], [72], [74], and continuous attempts for improved method development are ongoing. This stems from the need for rapid and accurate methods for the detection in one run of as many as possible of the antibiotics used as first and second lines of treatment in critically ill patients. Nonetheless, care must be taken during method development due to the difference in the physicochemical properties of the different antibiotics used in ICU. In comparison to stable antibiotics such as linezolid, β-lactams antibiotics are unstable and highly susceptible for degradation under different analytical settings. Reviewing the chemical characteristics of β-lactams antibiotics is beyond the scope of this review. However, as the current attempt is to optimize methods for the simultaneous analysis of different antibiotics with different reported stabilities it is necessary to consider the different parameters that might affect the stability of the antibiotics ahead of time. Consequently, this part will shed light on the key steps that have been recognized to be essential to improve the LC-MS/MS analysis of antibiotics used in critically ill patients with specific emphasis on β-lactams due to their instability.
Sample treatment
Sample cleanup procedures for β-lactam antibiotics include solid phase extraction [58], [60], [62], [67], [72], liquid-liquid extraction [59] and protein precipitation using acids [56], [61] and organic solvents i.e.: methanol or acetonitrile [64], [72], [74]. Even though the use of acidic solutions such as trichloroacetic acid (TCA) has been used successfully, care must be taken due to the instability of the four member β-lactam ring and its consequent degradation in high acid concentration [73], [75]. It seems, on the other hand, that the concentration of acid that increases the degradation is antibiotic dependent. For instance, while 6% and 30% TCA have been effectively used, respectively, for the extraction of cefdinir/cefexime [56] and ceftazidime [61], 10% TCA significantly affected the stability of other β-lactams particularly meropenem [74]. The stability of β-lactams is also significantly affected in the presence of zinc sulfate and, therefore, its use as a precipitant should be avoided [76]. Though protein precipitation with methanol and acetonitrile is frequently used, it seems that acetonitrile is preferred due to the great reproducibility it offers along with its lowest ionization suppression effect [64], [68], [74], [77]. Furthermore, due to the inherent instability of this class of antibiotics especially ring hydrolysis the use of stabilizing buffers has been recommended and in some cases was found as a necessity [23]. For instance, extraction of β-lactams in acetonitrile supplemented with 0.1% formic acid was found to be important to improve the stability of the samples [74]. Yet, while most β-lactams are stabilized with 0.1% FA, for others such as the highly unstable ertapenem the use of 2-(N-morpholino)-ethanesulfonic acid (MES) and 3-(N-morpholino)-propanesulfonic acid (MOPS) has been proved essential to maintain stability [23]. Whereas no further processing of the extracted samples is required if analytes’ separation is performed in hydrophilic interaction liquid chromatography (HILIC) mode [71]; another important step to perform prior to analysis is the dilution of the supernatant obtained after precipitation, whenever separation is performed in the reversed phase mode [68], [74], [78]. The dilution step is indispensable to ensure good peaks shape and to maintain the retention time of β-lactams [68], [74], [78]. Both water and water containing 0.1% formic acid are used. However, the use of the latter one may be more beneficial as it decreases the 24h degradation profile of meropenem [74], [79]. However, the fact that in the settings of TDM a fast delivery of the result is essential (hours and not days), improving the 24h stability profile is not a prerequisite, hence, the use of 0.1% FA to increase meropenem stability might not be relevant. As all of the aforementioned methods allow the determination of the total amount of antibiotics and not the free pharmacologically active concentrations, correction for protein binding is usually performed. While this approach is suitable for low protein binding antibiotics, the same cannot be applied for those with high protein binding characteristics and, therefore, is more affected by the pathological changes affecting critically ill patients as we will explain hereafter. The reported protein binding data for the antibiotics are made on analysis done in non-critically ill patients. Consequently, the estimation of the free unbound concentration from the total amount analyzed might result in over or under prediction of the true values especially that hypoalbuminemia is very common in critically ill patients [80], [81], [82]. A comparison between estimating the free drug concentrations from total values versus direct determination of the free unbound concentration was performed by Wong et al. on seven antibiotics that differ in their known percent of protein binding [82]. In their study Wong et al. [82] found that while estimation of the free drug concentration is not significantly different for meropemen, known to have a low fraction of protein binding, significant differences were noted for the highly protein-bound antibiotics such as ceftriaxone and flucloxacillin. Consequently, it was recommended to directly measure, instead of estimating, the free unbound concentrations [82]. However, it is worth mentioning that from all the currently published analytical methods only one method used ultracentrifugation for the analysis of free drug concentrations of β-lactam antibiotics [57]. For the time being direct determination of free drug concentration has not been widely adopted in methods intended for TDM and free drug levels estimation does not seem to hinder the successful application of the methods in improving the clinical outcome from the antimicrobial therapy of ICU patients. Nevertheless, more studies are warranted to ascertain to which extent direct free concentration determination is a requisite. Table 1, summarizes the protein binding of different classes of antibiotics used in ICU.
Reported percentage (%) of binding to plasma protein of 20 different antibiotics belonging to several classes (i.e.: β-lactams, cephalosporines, penicillins, oxalizidione, sulfamide, fluoroquinolones and colistin).
Antibiotic name | afb, % | Refs. |
---|---|---|
Low bound | ||
Ampicillin | 15–25 | [83], [84] |
Meropemen | 2; (1–10) | [85], [86], [87] |
Ceftolozane | <20 | [88] |
Ceftazidime | 15.5–17 | [87], [89], [90] |
Cefuroxime | 31.5 | [87] |
Linezolid | 31 | [91] |
Levofloxacin | 25–35 | [83] |
Ciprofloxacilin | 25–35; 39.6 | [83], [92] |
Piperacillin | 20–30 | [93] |
Tazobactam | 20–30 | [93] |
Moxifloxacin | 26 | [84] |
Moderatetaly bound | ||
Benzylpenicillin | 65; (55–65) | [83], [87] |
Sulfamethoxazole | 66; (40–50) | [83], [87] |
Trimethoprim | 40–50 | [83] |
Cefoxitine | 76.5 | [87] |
Highly bound | ||
Flucloxacillin | 94.7–96.2 | [94] |
Ceftriaxone | 93.8; (90–97) | [83], [87] |
Daptomycin | 90–94 | [95] |
Tigecyclin | 81.2–92.9 | [96] |
Colistin | 85.9–97.2 | [97] |
Antibiotics were grouped based on the extent of their protein binding: low (0%–40%), moderate (40%–70%), and highly bound (70%–99%). afb, fraction bound.
LC separation
Separation of β-lactam antibiotics have been performed on a wide variety of columns such as bridged ethylsiloxane/silica hybrid (BEH) C18, BEH HILIC, and high strength silica (HSS) T3 (C18) [64], [66], [71], [72]. On the other hand, it is worth mentioning that limited retention of β-lactam antibiotics on conventional reversed-phase C18 columns has been previously documented [63]. In most of the analytical methods separation of β-lactam and other classes of antibiotics rely on the use of a combination of water and acetonitrile or water and methanol. With respect to β-lactams the usefulness of methanol versus acetonitrile, during separation is still controversial. This is due, as previously reported, to their instability in methanol as compared to acetonitrile [98]. Nevertheless, it was suggested that when the chromatographic run time is less than 10 min, it is unlikely that the compounds undergo any degradation during this short run time [99]. As the effect of methanol on individual β-lactams (possibly differential effects) is lacking, further studies are warranted. In all cases, eluents are supplemented with small amounts of acids and salts, necessary to obtain reproducible peak areas as well as to improve ionization once the sample reaches the MS [78]. However, it is worth mentioning that although small amounts of acids have been used for the analysis of β-lactams, the presence of acids favors the formation of sodium adducts of other antibiotic such as sulfamethoxazole and in this case the use of acids is not highly recommended [67]. Consequently, it is important to find a compromise between separation efficiency and stability of the MS signal when it comes to the analysis of a mixture of antibiotics that differ in their physicochemical properties.
Tandem mass spectrometry (MS/MS)
Mass spectrometry, in negative or positive ionization mode, coupled to LC has been widely used for the identification of β-lactams and other antibiotics prescribed to critically ill patients. The power of MS is increased when coupled to LC which by ensuring a good separation of the compounds decreases the potential ion-suppression effects occurring by co-eluting compounds [73]. Even though due to their carboxylic acid moiety β-lactams are amenable to negative ionization [72] most of them have higher sensitivity in positive mode ionization [74]. Comparison between the different mass analyzers often used in MS shows that atmospheric pressure chemical ionization (APCI) interface is not suitable for β-lactams due to their decomposition at high temperatures. Despite the use of thermospray and electrospray ionization (ESI) interfaces, currently the latter one is the preferred interface due to the ease of β-lactams ionization [73]. ESI triple quadrupole instruments which enable tandem mass spectrometry (MS/MS) is the most often used [64], [66], [72], [74]. MS/MS has the power of increasing the selectivity and precision of compounds identifications and quantification. In many cases one specific fragment is followed. Yet, in order to achieve higher confidence and accuracy of identification when multiple compounds are analyzed at least two fragments must be detected. In general the most intense peak is used for quantification while the second one is used for identification [72], [73]. Due to the liability of the β-lactam ring, collision-induced fragmentation used in MS/MS leads to ring cleavage and, subsequently, one of the detected fragments is class-specific fragment (m/z 160) and the second is a compound specific daughter ion, i.e. [M+H-159]+ [73]. Internal standards are used to correct for any potential interference and to correct for sample loss during sample preparation [100]. Most of the currently published LC-MS/MS methods developed for the simultaneous quantification of β-lactams and other antibiotics use isotopically labeled antibiotics as internal standards. The use of labeled standards increases the accuracy and the fidelity of detection and quantification as the mass spectrometer will simultaneously separate and quantify the tracer and tracing molar ratios.
A summary of different LC conditions used for the simultaneous detection of several β-lactams and other antibiotics from human plasma is provided in Table 2. For each method a summary of the following is presented: antibiotics analyzed, sample cleanup, gradient, separation and columns used. The MS/MS settings used for the identification and quantification of antibiotics are presented in Table 3, which includes the ionization mode, the transitions, as well as the covered ranges.
Summary of liquid chromatography conditions used for the simultaneous extraction and separation of different β-lactam antibiotics prior to MS/MS.
Antibiotics | Sample cleanup/column | Mobile phase/gradient | Other parameters | Refs. |
---|---|---|---|---|
Amoxicillin ceftazidime cefuroxime meropenem piperacillin | – Protein precipitation with 6.6 fold ACN containing IS followed by 1:5 (v/v) dilution in H2O – Column: UPLC BEH C18 (100 mm×2.1 mm, 1.7 μm) +0.2 μm pre-column filter unit/a guard column | – Mobile phase: MPA: H2O (0.1%FA, 2 mM AmAc) MPB: MeOH (0.1% FA, 2 mM AmAc) – Gradient: 0–0.3 min: 2% MPB 0.4–0.5 min: 2%–98% MPB 0.5–1.5 min: 98% MPB 1.5–2.5 min: 2% MPB | – Flow rate: 0.4 mL/min – Total run time: 2.5 min – Injection volume: 40 μL – Column temperature: 50 °C | [64] |
Ampicillin, amoxicillin cefepime, ceftazidime cefazolin, cefuroxime cefadroxil, linezolid flucloxacillin, tazobactam meropenem, piperacillin phenoxymethylpenicillin | – Solid phase extraction – Column: Acquity HSS T3 (50 mm×2.1 mm, 1.7 μm) BEH C18 guard-column (5 mm×2.1 mm, 1.7 μm) | – Mobile phase: MPA: 5% ACN (1 mM FA, AmAc) MPB: ACN – Gradient: 0–1 min: 100% of MPA 1–2 min: 0%–21% MPB 3 min: system switched to 99% MPB 3–4 min: 99% MPB 4 min: 100% MPA | – Flow rate: 0.6 mL/min – Total run time: 4 min – Injection volume: 1 μL – Column temperature: 40 °C | [72] |
Ampicillin ceftazidime meropenem piperacillin tazobactam | – Protein precipitation with ACN (1:2, v/v) followed by dilution (1:1, v/v) in H2O (dichloromethane at (1:0.5, v/v) to partition the ACN and lipid-soluble plasma components) – Column: Acquity UPLC BEH C18 (100 mm×2.1 mm, 1.7 μm) +0.2 μm pre-column filter unit/a guard column | – Mobile phase: MPA: H2O (0.1% FA) MPB: ACN (0.1% FA) – Gradient: 0.0–0.5min: 5% MPB 0.5–4 min: 5%–55% MPB 4.0–4.5 min: 95% MPB 4.5–5.5 min: 5% MPB | – Flow rate: 0.4 mL/min – Total run time: 5.5 min – Injection volume: 10 μL – Column temperature: 50°C | [66] |
Benzylpenicillin ceftazidime cephazolin ertapenem flucloxacillin meropenem piperacillin | – Protein precipitation with ACN (1:2, v/v) followed by dilution (1:1, v/v) in H2O+0.1% FA – Column: kinetex® C18 with TMS endcaping (2.1 mm×50 mm, 2.6 μm) +pre-fitted in-line filter for column protection | – Mobile phase: MPA: H2O (0.1% FA) MPB: ACN (0.1% FA) – Gradient: 0.0–0.1 min: 0% MPB 0.1–2.0 min: 0%–85% MPB 2.0–5.5 min: 85% MPB 5.5–6.0 min: 85%–0% MPB 6.0–7.0 min: 0% MPB | – Flow rate: 0.3 mL/min – Total run time: 7.0 min – Injection volume: 20 μL – Column temperature: 35°C | [74] |
Amoxicillin ciprofloxacin linezolid moxifloxacin | – Protein precipitation with ACN (1:2, v/v) followed by dilution (1:3, v/v) in H2O+0.1% FA – Column: Atlantis dC18 (150 mm×2.0 mm, 3 μm) | – Mobile phase: MPA: H2O (0.1% FA) MPB: ACN (0.1% FA) | – Flow rate: 0.2 mL/min – Total run time: 13.0 min – Injection volume: 1 μL – Column temperature: 35°C | [68] |
– Gradient: 0–4 min: 20% MPB 4–5 min: 20%–80% MPB 5–8 min: 80% MPB 8–13 min: 20% MPB | ||||
Anidulafungin caspofungin fluconazol hydroxynitraconazole itraconazol posaconazol voriconazole voriconazol-n-oxide | – Protein precipitation with ACN/(0.5% FA) (1:2, v/v) followed by dilution (1:2, v/v) in MeOH/H2O (50:50, 0.1% FA) – Column: Acquity UPLC C18 (2.1 mm×30 mm, 1.7 μm) | – Mobile phase: MPA: H2O (0.1% FA, 10 mM AmFA) MPB: ACN (0.1% FA) – Gradient: 0.0–0.3 min: 2% MPB 0.3–0.5 min: 2% MPB 0.5–1.8 min: 40% MPB 1.8–4.7 min: 45% MPB 4.7–5.5 min: 95% MPB 5.5–7.0 min: 2% MPB | – Flow rate: 0.3 mL/min – Total run time: 7 min – Injection volume: 10 μL – Column temperature: 45°C | [65] |
Fosfomycin | – Protein precipitation with ACN (1:9, v/v) – Column: HILIC silica (150 mm×2.1 mm, 5 μm) +Guard column/silica filter (4 mm×2 mm) | – Mobile phase: MPA: H2O (0.05% FA, 0.1% AmFA) MPB: 90% ACN (0.05% FA, 0.1% AmFA, 10% MPA) – Gradient: 0–4 min: 0%–45% MPA 4–8.5 min: 55% MPB | – Flow rate: 0.3 mL/min – Total run time: 8.5 min – Injection volume: 10 μL – Column temperature: 35°C | [71] |
Colistin daptomycin vancomycin teicoplanin | – Protein precipitation with ACN (1:2, v/v) followed by dilution (1:9, v/v) in H2O+0.1% FA – Column: Kinetex C18 (2.1 mm×50 mm, 2.6 μm) | – Mobile phase: MPA: H2O (0.1% FA) MPB: ACN (0.1% FA) – Gradient: 0–2.5 min: 5%–100% MPB 2.5–6 min: 100% MPB 6–10 min: 5% MPB | – Flow rate: 0.3 mL/min – Total run time: 10min – Injection volume: 10 μL – Column temperature: 40°C | [78] |
Trimethoprim sulfamethoxazole | – Solid phase extraction – Column: Gemini C18 (150 mm× 4.6 mm, 5 μm) +C18 guard column (4.0 mm× 3.0 mm, 5 μm) | – Mobile phase: ACN/H2O (50:50, v/v) | – Flow rate: 2.5 mL/min – Total run time: 2.5 min – Injection volume: 5 μL – Column temperature: RT | [67] |
Amoxicillin cefazolin cefotaxime ceftriaxone da-cefotaxime | – Protein precipitation with cold ACN (1:4, v/v) followed by evaporation to dryness at 40°C under nitrogen gas flow and residue reconstitution in 100 μL of 0.1% FA – Column: Acquity UPLC BEH C18 | – Mobile phase: MPA: H2O (0.1% FA) MPB: MeOH (0.1% FA) – Gradient: 0–0.5 min: 20% MPB | – Flow rate: 0.4 mL/min – Total run time: 3.5 min – Injection volume: 10 μL – Column temperature: 40°C | [79] |
Meropenem vancomycin | (2.1 mm×100 mm, 1.7 μm) +0.2 μm pre-column filter | 0.5–1 min: 20%–40% MPB 1.0–2 min: 100% MPB 2.5–3 min: 20% MPB | ||
Cefepime ciproflaxin linezolid meropenem piperacillin tazobactam | – Protein precipitation with ACN (1:1), followed by dilution of 10 μL of the supernatant in 500 μL of (H2O/MeOH, 10:90 v/v) from which 200 μL were subjected to automated SPE – Column: Acquity UPLC BEH Phenyl (2.1 mm×100 mm, 1.7 μm) | – Mobile phase: MPA: H2O (0.1% FA) MPB: [MeOH/ACN, 75/25 (v/v)] – Gradient: 0–0.8 min: 10% MPB 0.8–1.0 min: 10%–45% MPB 1.0–2.0 min: 45% MPB 2.0–2.05 min: 45%–70% MPB 2.05–2.3 min: 70% MPB 2.3–2.4 min: 70%–90% MPB 2.4–4.2 min: 90% MPB 4.2–4.5 min: 90%–10% MPB 4.5–5.0 min: 10% MPB | – Flow rate: 0.3 mL/min – Total run time: 5 min – Injection volume: 7 μL – Column temperature: 50°C | [101] |
ACN, acetonitrile; IS, internal standard; H2O, water; MPA, mobile phase A; FA, formic acid; MPB, mobile phase B; MeOH, methanol; AmAc, ammonium acetate; RT, room temperature; AmFA, ammonium formate.
Summary of MS/MS conditions and covered ranges used for the simultaneous detection of several β-lactam and other antibiotics.
Antibiotics/internal standards | ESI mode | MS/MS transition (m/z) | Detection range, mg/L | Refs. | |
---|---|---|---|---|---|
Parent ion | Daughter ion | ||||
Ceftazidime | ESI + | 547.1 | 468.0 | 0.5–80 | [64] |
d5-Ceftazidime | ESI + | 552.0 | 468.0 | ||
Meropenem | ESI + | 384.2 | 141.2 | 0.5–80 | |
d6-Meropenem | ESI + | 390.2 | 147.0 | ||
Piperacillin | ESI + | 518.2 | 143.1 | 1.0–150 | |
d5-Piperacillin | ESI + | 523.3 | 148.1 | ||
Amoxicillin | ESI + | 366.1 | 114.0 | 1.0–100 | |
d4-Amoxicillin | ESI + | 370.2 | 114.0 | ||
Cefuroxime | ESI + | 442.2 | 364.1 | 1.0–100 | |
d3-Cefuroxime | ESI + | 445.1 | 367.1 | ||
Piperacillin | ESI + | 519.0 | 143.1 | 0.1–50 | [74] |
Benzylpenicillin | ESI + | 335.6 | 160.2 | 0.1–50 | |
Flucloxacillin | ESI + | 454.6 | 160.1 | 0.25–50 | |
Meropenem | ESI + | 384.3 | 114.1 | 0.1–50 | |
Ceftazidime | ESI + | 547.2 | 167.1 | 0.1–50 | |
Ertapenem | ESI + | 476.9 | 432.9 | 0.1–50 | |
Cephazolin | ESI + | 455.4 | 156.1 | 0.1–50 | |
Fluconazole (IS) | ESI + | 307.3 | 127.1 | ||
Vancomycin | ESI + | 724.7 | 144.0 | 0.50–100.0 | [78] |
724.7 | 99.9 | ||||
Daptomycin | ESI + | 810.9 | 313.1 | 0.50–100.0 | |
810.9 | 158.9 | ||||
Polymyxin B1 (IS) | ESI + | 401.9 | 101.0 | ||
401.9 | 241.1 | ||||
Ciprofloxacin | ESI + | 332.0 | 231.2 | 0.20–10.0 | [68] |
Linelozid | ESI + | 338.8 | 296.0 | 0.40–20.0 | |
Moxifloxacin | 402.2 | 384.0 | 0.20–10.0 | ||
Amoxicillin | ESI + | 366.0 | 114.0 | 0.40–20.0 | |
d4-Moxifloxacin | ESI + | ||||
Sulfamethoxazol | ESI + | 253.96 | 108.07 | 0.50–60.0 | [67] |
Trimethoprim | ESI + | 291.02 | 230.02 | 0.05–5.0 | |
Benznidazole (IS) | ESI + | 261.41 | 91.30 | ||
Amoxicillin | ESI + | 366.10 | 349.10 | 0.2–80 | [79] |
Meropenem | ESI + | 384.20 | 68.00 | 0.2–80 | |
Cefazolin | ESI + | 455.00 | 323.00 | 0.2–25 | |
Cefotaxime | ESI + | 456.00 | 324.00 | 0.2–100 | |
Deacetylcefotaxime | ESI + | 414.00 | 285.10 | 0.2–100 | |
Ceftriaxone | ESI + | 554.90 | 396.00 | 2.0–360 | |
Vancomycin | ESI + | ||||
Oxacillin | ESI + | 725.30 | 143.80 | 0.7–70 | |
ESI + | 402.00 | 243.10 |
Antibiotics/internal standards | Ion mode | MS/MS transition (m/z) | Detection range, mg/L | Refs. | |
---|---|---|---|---|---|
Parent ion | Daughter ion | ||||
Ampicillin | ESI − | 348.3 | 206.6 | 0.58–70.05 | [72] |
Piperacillin | ESI − | 516.0 | 329.9 | 0.32–38.06 | |
Flucloxacillin | ESI − | 452.1 | 310.6 | 0.08–9.11 | |
Cefuroxime | ESI + | 423.3 | 317.8 | 0.48–57.69 | |
Phenoxymethlpenicillin | ESI − | 349.1 | 207.8 | 0.06–7.28 | |
d5-Phenoxymethyl-penicillin | ESI − | 354.3 | 212.7 | ||
Meropenem | ESI + | 384.4 | 253.7 | 0.17–20.06 | |
d6-Meropenem | ESI + | 390.4 | 259.8 | ||
Ceftazidime | ESI + | 547.1 | 468.1 | 0.76–90.81 | |
Cefepime | ESI + | 481.1 | 323.7 | 0.18–21.53 | |
13C, d3-Cefepime | ESI + | 485.5 | 327.6 | ||
Tazobactam | ESI + | 300.8 | 167.7 | 0.24–27.24 | |
Cefazolin | ESI + | 455.2 | 322.6 | 0.61–73.01 | |
Cefadroxil | ESI + | 364.2 | 207.7 | 0.05–6.04 | |
d4-Cefadroxil | ESI + | 368.4 | 212.1 | ||
Amoxicillin | ESI – | 364.2 | 222.6 | 0.43–51.05 | |
d4-Amoxicillin | ESI − | 368.3 | 227.2 | ||
Caspofungin | ESI + | 547.2 | 86.0 | 0.06–30.0 | [65] |
547.2 | 131.0 | ||||
547.2 | 137.0 | ||||
547.2 | 538.7 | ||||
Anidulafungin | ESI + | 1140.9 | 343.0 | 0.10–12.0 | |
1140.9 | 388.0 | ||||
1140.9 | 1122.5 | ||||
Fluconazole | ESI + | 307.0 | 238.1 | 0.10–50.0 | |
Fluconazole-d4 | ESI + | 311.1 | 242.2 | ||
Voriconazole | ESI + | 350.1 | 281.2 | 0.02–10.0 | |
Voriconazole-d3 | ESI + | 353.1 | 284.2 | ||
Itraconazole | ESI + | 705.4 | 392.2 | 0.02–10.0 | |
705.4 | 432.4 | ||||
Itraconazole-d5 | ESI + | 710.5 | 397.3 | ||
Posaconazole | ESI + | 701.4 | 127.0 | 0.02–10.0 | |
701.4 | 683.3 | ||||
Posaconazole-d4 | ESI + | 705.4 | 354.0 | ||
Piperacillin | ESI + | 518 | 160/(143:Q) | 0.5–60 | [101] |
d5-Piperacillin | ESI + | 523 | 160 | ||
Cefepime | ESI + | 241 | 227 | 0.13–50 | |
13C, d3-Cefepime | ESI + | 243 | 227 | ||
Tazobactam | ESI + | 301 | 168 | 0.25–20 | |
Meropenem | ESI + | 384 | 141/(114:Q) | 0.25–50 | |
d6-Meropenem | ESI + | 390 | 147 | ||
Linezolid | ESI + | 338 | 296/(195:Q) | 0.1–32 | |
d3- Linezolid | ESI + | 341 | 297 | ||
Ciprofloxacin | ESI + | 332 | 231/(245:Q) | 0.05–8 | |
d8-Ciprofloxacin | ESI + | 340 | 235 |
Q, Qualifier; ESI, electrospray ionization.
Popular antibiotics measured by LC-MS/MS
A thorough evaluation/comparison of the developed methods and the types of the studied antibiotics shows that in the 11 described methods 37 antibiotics belonging to different classes have been analyzed, yet at different rates. A ranking of the different antibiotics according to the frequency of their inclusion in the developed methods is highlighted in Table 4. Eight of the 11 described methods share, although to a different extent, the analysis of 13 out of 37 antibiotics. Meropenem and piperacillin are the most prevalent antibiotics being common in six and five analytical methods, respectively, while the others are shared in two to four methods (Table 4). The enormous popularity of meropenem and piperacillin is not unexpected. These broad spectrum antibiotics are primarily used as a first line of treatment in ICU patients followed by narrower spectrum antibiotics when the type of infection and resistance are identified [102]. Secondly, the levels of these antibiotics are recurrently found to vary extensively, in critically ill patients, which classify them as important targets for TDM (Table 5). Table 5 presents a quick overview about the current reported variability of the trough levels and maximum levels of the most studied antibiotics as observed in ICU patients and therefore, emphasize the clinical relevance of their selection for TDM. A more extensive ranking of the different antibiotics is beyond the scope of this review as published surveys show that the type and extent of use of antibiotics differ between countries, type of infection and known resistance [107], [108]. Nevertheless, a brief analysis of the current use of antibiotics in Germany shows that β-lactams are widely used in ICU in University hospitals [107]. The median RDD/100 of the different classes of β-lactams is as follows: carbapenem (3.7), extended-spectrum penicillin (5.9), third/fourth generation cephalosporin (4.3), first/second generation cephalosporin (8.0), aminopenicillin/β-lactamase inhibitors (6.5), and narrow-spectrum penicillin (1.9). Among the other prescribed antibiotics fluoroquinolones have the highest RDD/100 (8.0) which continues to be prescribed mainly to elderly people [107]. To have an overview about the global use of antibiotics readers are referred to a recent survey supplied by the Center for Disease Dynamics (https://cddep.org/sites/default/files/swa_2015_final.pdf).
Antibiotics ranked according to the frequency of their selection in methods intended for therapeutic drug monitoring.
Antibiotics | Refs. |
---|---|
Meropenem | [64], [66], [72], [74], [79], [101] |
Piperacillin | [64], [66], [72], [74], [101] |
Ceftazidime | [64], [66], [72], [74] |
Amoxicillin | [64], [68], [72], [79] |
Tazobactam | [66], [72], [101] |
Cefazolin | [72], [74], [79] |
Linezolid | [68], [72], [101] |
Ciprofloxacin | [68], [101] |
Ampicillin | [66], [72] |
Flucloxacillin | [72], [74] |
Cefepime | [72], [101] |
Cefuroxime | [64], [72] |
Vancomycin | [78], [79] |
Studies reporting the large variability in the levels of several antibiotics used to treat critically ill patients in intensive care units.
Antibiotics | Cmin; (median), mg/L | Refs. | Antibiotics | Cmax; (median), mg/L | Refs. |
---|---|---|---|---|---|
Meropenem | 0.87–0.89 | [103] | Meropenem | 17.58 | [103] |
3.0 ± 0.9 | [30] | 24.5 ± 7.2 | [30] | ||
4.4–17.5; (11) | [104] | ||||
Piperacillin | 4.9–98.0 | [14] | Sulfamethoxazole | 80.80 decreased to 15.2 | [34] |
19.7–70.0; (38.5) | [104] | ||||
<1–156.3; (11.9) | [105] | ||||
Flucloxacillin | 0.2–0.4 | [36] | Trimethoprim | 7.51 decreased to 2.7 | [34] |
Linezolid | <0.13–14.49; (2.06) | [33] | Linezolid | 10±3.7 | [106] |
1.7 ± 1.1 | [106] | ||||
Cefepime | <1–7.7; (1.8) | [29] | Ciprofloxacin | 0.7–6.6; 2.81 | [9] |
Cmin, trough concentration; Cmax, maximum concentration.
Conclusions and future prospects
Overcoming the pathophysiological changes affecting the PK/PD target attainment of the current antimicrobial therapy in ICU patients is the focus of intense investigations with the main intention of improving clinical outcome. This incorporates ensuring that the required antibiotic level is maintained to penetrate the site of infection, prevent resistance, and avoid toxicity-related to antibiotic accumulation. This is particularly significant for cancer patients suffering from severe infections, found to be associated with their increased mortality rate. Furthermore, an increase in the awareness regarding potential antineoplastic-antibiotic interactions would spare cancer patients from the occurrence of additional unnoticed reasons for toxicity. To improve the clinical outcome from the current therapy regimen TDM seems to offer a basis on which clinicians can adjust and personalize the treatment. When sample throughput is important such as in TDM the development of a reliable method with short analysis time becomes essential. Immunoassays, which are easy to perform and can be accessible worldwide, are not available for all classes of antibiotics and attempts to establish immunoassays for β-lactams have proved to be difficult due to the reactivity or degradation of the β-lactam ring. Fortunately, the ongoing advances in the available analytical methods render the application of these techniques for TDM of β-lactams and many other antibiotics more feasible. LC-MS/MS method, through accurate and rapid antibiotics detection along with the availability of isotopically labeled internal standards that increase the fidelity of the analysis, has become the method of choice. Different analytical methods have been published, yet, due to the different characteristics of β-lactams and other antibiotics used in ICU, the establishment of one single method is not possible for the time being. Additional concern is the reliability of the estimation of the free pharmacologically drug concentration from the total detected concentrations. Yet, more studies are needed in that direction to rule out the best strategy to be used in the future. There is no doubt that with the ongoing advancement in analytical method developments many of the encountered difficulties will be overcome and will add more to our understanding in improving the clinical outcome from the antimicrobial therapy of ICU/cancer patients. Furthermore, both TDM and an increase in the collaboration between clinicians, pharmacists and general practitioners as well as the use of computer-based medication prescription systems in hospitals will help to avoid and notice the frequently unnoticed drug-drug interactions.
Author contributions: All authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: El-Najjar is funded by a fellowship for senior scientists from the “Bayerisches Programm zur Realisierung der Chancengleichheit für Frauen in Forschung und Lehre”.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.
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©2017 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Editorial
- Mass spectrometry or immunoassay: est modus in rebus
- Reviews
- The use of liquid chromatography-tandem mass spectrometry for therapeutic drug monitoring of antibiotics in cancer patients
- Tackling serum folate test in European countries within the health technology assessment paradigm: request appropriateness, assays and health outcomes
- Genetics and Molecular Diagnostics
- Genetic diagnosis of α1-antitrypsin deficiency using DNA from buccal swab and serum samples
- General Clinical Chemistry and Laboratory Medicine
- Serum triglyceride measurements: the commutability of reference materials and the accuracy of results
- Variant peptide detection utilizing mass spectrometry: laying the foundations for proteogenomic identification and validation
- Evaluation of two fully automated immunoassay based tests for the measurement of 1α,25-dihydroxyvitamin D in human serum and comparison with LC-MS/MS
- Parallel diurnal fluctuation of testosterone, androstenedione, dehydroepiandrosterone and 17OHprogesterone as assessed in serum and saliva: validation of a novel liquid chromatography-tandem mass spectrometry method for salivary steroid profiling
- Determination of oxycodone and its major metabolites noroxycodone and oxymorphone by ultra-high-performance liquid chromatography tandem mass spectrometry in plasma and urine: application to real cases
- Identification and quantitation of phosphatidylethanols in oral fluid by liquid chromatography-tandem mass spectrometry
- Relationship between plasma and salivary melatonin and cortisol investigated by LC-MS/MS
- Paramagnetic micro-particles as a tool for rapid quantification of apixaban, dabigatran, edoxaban and rivaroxaban in human plasma by UHPLC-MS/MS
- Measurements of serum non-ceruloplasmin copper by a direct fluorescent method specific to Cu(II)
- The serum concentrations of leptin and MCP-1 independently predict low back pain duration
- Immunoassay screening in urine for synthetic cannabinoids – an evaluation of the diagnostic efficiency
- Cancer Diagnostics
- Study of kallikrein-related peptidase 6 (KLK6) and its complex with α1-antitrypsin in biological fluids
- Cardiovascular Diseases
- A candidate liquid chromatography mass spectrometry reference method for the quantification of the cardiac marker 1-32 B-type natriuretic peptide
- The natriuretic peptide MR-proANP predicts all-cause mortality and adverse outcome in community patients: a 10-year follow-up study
- CASZ1 loss-of-function mutation contributes to familial dilated cardiomyopathy
- Diabetes
- Evaluating new HbA1c methods for adoption by the IFCC and NGSP reference networks using international quality targets
- Infectious Diseases
- Analytical and diagnostic performance of two automated fecal calprotectin immunoassays for detection of inflammatory bowel disease
- Letters to the Editor
- Is fasting necessary for lipid profile determinations? Some considerations from the perspective of the clinical laboratory
- Precision of nonfasting lipid profiles should focus on clinical relevance rather than necessarily obtaining the least variation
- Triglyceride concentrations should be measured after elimination of free glycerol to exclude interindividual variations due to adiposity and fasting status
- Estimation of the reference interval for serum folate measured with assays traceable to the WHO International Standard
- Implausible elevation of peripheral thyroid hormones during therapy with a protein supplement
- Interference in Na+ measurements on the Siemens RAPIDPoint® 500 after nortriptyline intoxication: a case report
- Usefulness of maternal red cell antibodies to predict hemolytic disease of the fetus and newborn and significant neonatal hyperbilirubinemia: a retrospective study
- Improvement of the Sandell-Kolthoff reaction method (ammonium persulfate digestion) for the determination of iodine in urine samples
- Clinical use of targeted high-throughput whole-genome sequencing for a dengue virus variant
Artikel in diesem Heft
- Frontmatter
- Editorial
- Mass spectrometry or immunoassay: est modus in rebus
- Reviews
- The use of liquid chromatography-tandem mass spectrometry for therapeutic drug monitoring of antibiotics in cancer patients
- Tackling serum folate test in European countries within the health technology assessment paradigm: request appropriateness, assays and health outcomes
- Genetics and Molecular Diagnostics
- Genetic diagnosis of α1-antitrypsin deficiency using DNA from buccal swab and serum samples
- General Clinical Chemistry and Laboratory Medicine
- Serum triglyceride measurements: the commutability of reference materials and the accuracy of results
- Variant peptide detection utilizing mass spectrometry: laying the foundations for proteogenomic identification and validation
- Evaluation of two fully automated immunoassay based tests for the measurement of 1α,25-dihydroxyvitamin D in human serum and comparison with LC-MS/MS
- Parallel diurnal fluctuation of testosterone, androstenedione, dehydroepiandrosterone and 17OHprogesterone as assessed in serum and saliva: validation of a novel liquid chromatography-tandem mass spectrometry method for salivary steroid profiling
- Determination of oxycodone and its major metabolites noroxycodone and oxymorphone by ultra-high-performance liquid chromatography tandem mass spectrometry in plasma and urine: application to real cases
- Identification and quantitation of phosphatidylethanols in oral fluid by liquid chromatography-tandem mass spectrometry
- Relationship between plasma and salivary melatonin and cortisol investigated by LC-MS/MS
- Paramagnetic micro-particles as a tool for rapid quantification of apixaban, dabigatran, edoxaban and rivaroxaban in human plasma by UHPLC-MS/MS
- Measurements of serum non-ceruloplasmin copper by a direct fluorescent method specific to Cu(II)
- The serum concentrations of leptin and MCP-1 independently predict low back pain duration
- Immunoassay screening in urine for synthetic cannabinoids – an evaluation of the diagnostic efficiency
- Cancer Diagnostics
- Study of kallikrein-related peptidase 6 (KLK6) and its complex with α1-antitrypsin in biological fluids
- Cardiovascular Diseases
- A candidate liquid chromatography mass spectrometry reference method for the quantification of the cardiac marker 1-32 B-type natriuretic peptide
- The natriuretic peptide MR-proANP predicts all-cause mortality and adverse outcome in community patients: a 10-year follow-up study
- CASZ1 loss-of-function mutation contributes to familial dilated cardiomyopathy
- Diabetes
- Evaluating new HbA1c methods for adoption by the IFCC and NGSP reference networks using international quality targets
- Infectious Diseases
- Analytical and diagnostic performance of two automated fecal calprotectin immunoassays for detection of inflammatory bowel disease
- Letters to the Editor
- Is fasting necessary for lipid profile determinations? Some considerations from the perspective of the clinical laboratory
- Precision of nonfasting lipid profiles should focus on clinical relevance rather than necessarily obtaining the least variation
- Triglyceride concentrations should be measured after elimination of free glycerol to exclude interindividual variations due to adiposity and fasting status
- Estimation of the reference interval for serum folate measured with assays traceable to the WHO International Standard
- Implausible elevation of peripheral thyroid hormones during therapy with a protein supplement
- Interference in Na+ measurements on the Siemens RAPIDPoint® 500 after nortriptyline intoxication: a case report
- Usefulness of maternal red cell antibodies to predict hemolytic disease of the fetus and newborn and significant neonatal hyperbilirubinemia: a retrospective study
- Improvement of the Sandell-Kolthoff reaction method (ammonium persulfate digestion) for the determination of iodine in urine samples
- Clinical use of targeted high-throughput whole-genome sequencing for a dengue virus variant