The value of incorporating patient-consulted medication reconciliation in influencing drug-related actions in the outpatient rheumatology setting.

BACKGROUND: Unintentional changes to patients' medicine regimens and drug non-adherence are discovered by medication reconciliation. High numbers of outpatient visits and medication reconciliation being time-consuming, make it challenging to perform medication reconciliation for all outpatients. Therefore, we aimed to get insight into the proportion of outpatient visits in which information obtained with medication reconciliation led to additional drug-related actions. METHODS: In October and November 2018, we performed a cross-sectional observational study at the rheumatology outpatient clinic. Based on a standardized data collection form, outpatient visits were observed by a pharmacy technician trained to observe and report all drug-related actions made by the rheumatologist. Afterwards, the nine observed rheumatologists and an expert panel, consisting of two rheumatologists and two pharmacists, were individually asked which drug information reported on the drug list composed by medication reconciliation was required to perform the drug-related actions. The four members of the expert panel discussed until consensus was reached about their assessment of the required information. Subsequently, a researcher determined if the required information was available in digital sources: electronic medical record (electronic prescribing system plus physician's medical notes) or Dutch Nationwide Medication Record System. RESULTS: Of the 114 selected patients, 83 (73%) patients were included. If both digital drug sources were available, patient's input during medication reconciliation resulted in additional information to perform drug-related actions according to the rheumatologist in 0% of the visits and according to the expert panel in 14%. If there was only access to the electronic medical record, the proportions were 8 and 29%, respectively. Patient's input was especially required for starting a new drug and discussing drug-related problems. CONCLUSIONS: If rheumatologists only had access to the electronic medical record, in 1 out of 3 visits the patient provided additional information during medication reconciliation which was required to perform a drug-related action. When rheumatologists had access to two digital sources, patient's additional input during medication reconciliation was at most 14%. As the added value of patient's input was highest when rheumatologists prescribe a new drug and/or discuss a drug-related problem, it may be considered that rheumatologists only perform medication reconciliation during the visit when performing one of these actions.

Dosing and Exposure of Vancomycin With Continuous Infusion: A Retrospective Study.

Vancomycin continuous infusion (CI) has suggested benefits over intermittent infusion: reduced nephrotoxicity, higher target attainment, and simpler therapeutic drug monitoring (TDM). Empiric dosing regimens range from 30-60 mg/kg/day and it is unclear which regimen results in optimal exposure. This study evaluates whether a dosing regimen of 45 mg/kg/day after a 20 mg/kg loading dose for patients with estimated glomerular filtration rate (eGFR) ≥ 50 mL/min results in adequate exposure. We retrospectively analyzed plasma concentrations from patients treated with vancomycin CI as routine clinical care between February and October 2021. Patients under 18 years old, with renal replacement therapy, reduced creatinine clearance (Chronic Kidney Disease Epidemiology Collaboration < 50 mL min/1.73 m2 ) or outpatient antibiotic therapy were excluded. Dose, renal function, and blood draw procedures were assessed for each measured vancomycin sample. Initially, 121 samples were included. Subsequently, 7 samples, 6 of which with concentrations ≥ 40 mg/L, were verified to be incorrectly drawn and excluded. With doses of 40-50 mg/kg/day concentrations ranged from 18.4-61.0 mg/L. Only 25% were within the target window of 17-25 mg/L and 15% were ≥ 40 mg/L. Supratherapeutic concentrations were observed in 89% of samples from patients dosed 40-60 mg/kg/day with eGFR 50-80 mL/min. Concluding, an empiric dosing regimen of 45 mg/kg results in too high vancomycin exposure and thus we recommend lower doses and differentiation according to renal function. Additionally, when measuring concentrations over 40 mg/L incorrect sampling must be excluded before dose adjustment and the large variability in exposure between patients, warrants the need for swift TDM.

Serum degradome markers for the detection of breast cancer.

Many proteins have been proposed as potential biomarkers for breast cancer. Yet, validation of their discriminative value using quantitative methods has scarcely been performed. In this study, we investigated the discriminative value of six peptides that were previously proposed to be generated by breast cancer specific exoproteases: bradykinin, des-Arg(9)-bradykinin, Hyp(3)-bradykinin, and fragments of fibrinogen alpha-chain (Fib-alpha ([605-629])), complement component 4a (C4a ([1337-1350])), and interalpha trypsin inhibitor heavy chain 4 (ITIH4 ([666-687])). Their absolute serum concentrations were measured with a completely validated liquid chromatography-tandem mass spectrometric assay (LC-MS/MS) and compared between 62 newly diagnosed breast cancer patients and 62 controls matched for age and sample storage duration. Both ITIH4 ([666-687]) and des-Arg(9)-bradykinin showed statistically significantly higher median concentrations in breast cancer samples than in matched control samples. Additionally, we analyzed serum samples collected after surgical removal of the tumor, in which median ITIH4 ([666-687]) and des-Arg(9)-bradykinin concentrations were significantly decreased and not statistically significantly different from concentrations in the controls anymore. In a combined analysis, ITIH4 (666-687]) and des-Arg(9)-bradykinin independently contributed to the discrimination between cases and controls. In this study, we confirmed that the exoprotease breakdown peptides, ITIH4 (666-687]) and des-Arg(9)-bradykinin, differed between breast cancer cases and controls, supporting the potential of degradome markers for the diagnosis of breast cancer.

Analysis of mass spectrometry data using sub-spectra.

BACKGROUND: Spectra resulting from Surface-Enhanced Laser Desorption/Ionisation (SELDI) mass spectrometry measurements are constructed by combining sub-spectra, each of which are the result of a single firing of the laser responsible for the process of desorption/ionisation. These firings are performed at different locations of the spot on which the sample is analysed. The final spectrum is then constructed by summing over all these sub-spectra. This process is sub-optimal in that it can average out peaks from peptides that are present in low abundance or are unevenly distributed across the spot, particularly because the amount of noise varies considerably between sub-spectra. This argues for analysing sub-spectra separately and combining results afterwards. RESULTS: Here, we propose to analyse these sub-spectra one-by-one and combine the results using a framework which includes a significance test. This allows one to, for the first time, attach a confidence measure to detected peaks, based on the signal strength of a peak across sub-spectra. In a comparison with three other approaches the sub-spectral approach achieves a higher sensitivity and a low FDR. We further introduce the notion of peak-bags, which provide rich information about the sub-spectral contributions to a given peak. CONCLUSION: The proposed procedure offers better control over the process of distinguishing signal from noise, resulting in an improved performance over other available methods. Moreover, our method provides an implicit deconvolution of peaks, yielding insight in the actual shape of a peak, potentially aiding in a deeper understanding of peak distribution. AVAILABILITY: Implementations of the algorithm in R are available upon request.

Identification of two new serum protein profiles for renal cell carcinoma.

Renal cell carcinoma (RCC) is the most lethal urological cancer, and survival greatly depends on early diagnosis. Therefore, reliable, new biomarkers for detection of RCC are required. We assessed serum protein profiles of samples from two institutes with SELDI-TOF MS in duplicate on CM10 chips at pH 6.0 (set 1: 37 RCC + 32 healthy controls (HC), set 2: 20 RCC + 25 HC). Mean peak intensities of detected proteins were compared between RCC and HC with non-parametric testing. Classification trees were built with discriminating peaks using one sample set as training set and the other as independent validation set. We found 15 peaks significantly different (p<0.01) between RCC and HC. Two classification trees could be built with these peaks. Tree A achieved 75% sensitivity and 85% specificity for cross-validation and 76 and 65% for independent validation. Tree B had 71 and 62% sensitivity and specificity for cross-validation and 83 and 82% for independent validation. Although two serum protein profiles comprising 5 protein peaks were found that could separate RCC from HC, the sensitivity and specificity is not sufficient to recommend large scale use. Upon structural identification and quantitative validation, however, these proteins might prove suitable markers in the follow up of RCC patients.

Clinical proteomics: searching for better tumour markers with SELDI-TOF mass spectrometry.

Recently, the focus of cancer research has expanded from genetic information in the human genome to protein expression analyses. Because this 'proteome' reflects the state of a cell, tissue or organism more accurately, much is expected from proteomics to yield better tumour markers for disease diagnosis and therapy monitoring. Some current proteomic technologies are particularly suitable for protein profiling in the search for new biomarkers. Surface-enhanced laser desorption ionization time-of-flight mass spectrometry has been used frequently, highlighting many new proteins as biomarkers (e.g. for ovarian, breast, prostate and colorectal cancer). However, it is becoming increasingly recognized that reproducibility and validation of these biomarkers should be addressed carefully, as should their origin and identity. If these efforts are made, protein profiling can contribute to the better diagnosis of patients and the optimization of their treatment.

Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry.

AIM: To detect the new serum biomarkers for colorectal cancer (CRC) by serum protein profiling with surface-enhanced laser desorption ionisation--time of flight mass spectrometry (SELDI-TOF MS). METHODS: Two independent serum sample sets were analysed separately with the ProteinChip technology (set A: 40 CRC+49 healthy controls; set B: 37 CRC+31 healthy controls), using chips with a weak cation exchange moiety and buffer pH 5. Discriminative power of differentially expressed proteins was assessed with a classification tree algorithm. Sensitivities and specificities of the generated classification trees were obtained by blindly applying data from set A to the generated trees from set B and vice versa. CRC serum protein profiles were also compared with those from breast, ovarian, prostate, and non-small cell lung cancer. RESULTS: Mass-to-charge ratios (m/z) 3.1x10(3), 3.3x10(3), 4.5x10(3), 6.6x10(3) and 28x10(3) were used as classifiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%. Most of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3x10(3), main classifier in most trees, was a doubly charged form of the 6.6x10(3)-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1x10(3) was identified as an N-terminal fragment of albumin, and m/z 28x10(3) as apolipoprotein A-I. CONCLUSION: SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring.

Evaluation of human neutrophil peptide-1, -2 and -3 as serum markers for colorectal cancer.

Increased total serum concentrations of human neutrophil peptide-1, -2 and -3 (HNP-1, -2 and -3) have been associated with colorectal cancer (CRC). Owing to a recently developed and fully validated liquid-chromatography coupled to tandem-mass spectrometry (LC-MS/MS) assay, individual serum concentrations of these antimicrobial peptides were quantified to evaluate their role as serum markers in CRC. Serum was obtained from patients with indications for colonoscopy, subsequently diagnosed as normal colon or hyperplastic polyp (CON; n= 368), adenomatous polyp (AP; n = 179) or colorectal cancer (CRC; n = 69). Comparison of HNP-1, -2 and -3 concentrations between CRC and CON (130 ± 90 vs. 105 ± 80; 264 ± 140 vs. 206 ± 99 and 62 ± 56 vs. 54 ± 59 for HNP-1, -2 and -3, respectively) revealed that reported up-regulated total HNP-concentrations can be largely attributed to increased HNP-2 (P=0.0006) and HNP-1 (P=0.024) levels. Although receiver operating characteristics (ROC) analyses showed low specificity of the peptides for CRC and no significant changes in serum levels were observed after surgical removal of the tumor (n=23), the established differentiation between the HNP-subtypes may be particularly useful to completely elucidate the role of these antimicrobial peptides in CRC.

Serum proteomics and disease-specific biomarkers of patients with advanced gastric cancer.

Gastric cancer is a commonly diagnosed solid tumor which is associated with a dismal prognosis making early diagnosis essential. Thus, this study aimed to identify novel biomarkers in gastric cancer. Serum of patients with advanced gastric cancer was collected according to a predefined schedule: prior to first-line chemotherapy with epirubicin (50 mg/m(2), day 1), cisplatin (60 mg/m(2), day 1) and capecitabine (1,000 mg/m(2), twice daily on days 1-14). The serum was collected serially before the treatment cycles and then analyzed by SELDI-TOF MS. Normal control subjects were matched according to age, gender and serum collection. Serum proteomic mass spectrometry data of all subjects were processed using the tbimass R-package and compared. We analyzed i) whether proteomic profile changes were associated with a response to chemotherapy and survival, and ii) whether changes in proteomic profiles occurring during the time period of chemotherapy were associated with tumor response. In total, 82 patients with adenocarcinoma of the stomach (mean age 57 years, males 69.5%) were treated with a mean number of five chemotherapy cycles. The overall tumor response rate, complete and partial remission combined, was 37%, median time to progression was 7 months (95% CI, 6-8) and median overall survival 11 months (95% CI, 9.5-12). By comparing 77 serum samples of patients with normal matched controls, we identified 32 proteins which discriminated the two groups. By selecting the most differentiating proteins, we built a classification model that correctly categorized 81% of the gastric cancer patients and 90% of the normal controls. Furthermore, we found a statistically significant correlation between the pre-treatment intensity of serum amyloid-α (SAA) and overall survival in gastric cancer patients, whereby a low intensity of SAA predicted a longer patient survival. A classification model, based on the 32 most discriminating proteins differentiating gastric cancer from normal controls, correctly classified subjects with relatively high sensitivity and specificity.

Detection of Colorectal Cancer by Serum and Tissue Protein Profiling: A Prospective Study in a Population at Risk.

Colorectal cancer (CRC) is the second most common cause of cancer-related death in Europe and its prognosis is largely dependent on stage at diagnosis. Currently, there are no suitable tumour markers for early detection of CRC. In a retrospective study we previously found discriminative CRC serum protein profiles with surface enhanced laser desorption ionisation-time of flight mass spectrometry (SELDI-TOF MS). We now aimed at prospective validation of these profiles. Additionally, we assessed their applicability for follow-up after surgery and investigated tissue protein profiles of patients with CRC and adenomatous polyps (AP). Serum and tissue samples were collected from patients without known malignancy with an indication for colonoscopy and patients with AP and CRC during colonoscopy. Serum samples of controls (CON; n = 359), patients with AP (n = 177) and CRC (n = 73), as well as tissue samples from AP (n = 52) and CRC (n = 47) were analysed as described previously. Peak intensities were compared by non-parametric testing. Discriminative power of differentially expressed proteins was assessed with support vector machines (SVM). We confirmed the decreased serum levels of apolipoprotein C-1 in CRC in the current population. No differences were observed between CON and AP. Apolipoprotein C-I levels did not change significantly within 1 month post-surgery, although a gradual return to normal levels was observed. Several proteins differed between AP and CRC tissue, among which a peak with similar mass as apolipoprotein C-1. This peak was increased in CRC compared to AP. Although we prospectively validated the serum decrease of apolipoprotein C-1 in CRC, serum protein profiles did not yield SVM classifiers with suitable sensitivity and specificity for classification of our patient groups.

Validation of SELDI-TOF MS serum protein profiles for renal cell carcinoma in new populations.

Currently, no suitable biomarker for the early detection or follow-up of renal cell carcinoma (RCC) is available. We aimed to validate previously reported potential serum biomarkers for RCC obtained with Surface Enhanced Laser Desorption Ionisation-Time of Flight Mass Spectrometry (SELDI-TOF MS) in our laboratory using distinct patient populations. Two sets of sera from RCC patients and healthy controls (HC) were gathered from different institutes and analysed according to published procedures. The first set (40 RCC, 32 HC) consisted of mainly presurgery samples from patients with disease stages I-IV. The second set (26 RCC, 27 HC) were mostly sera from patients with stage-IV disease, drawn after nephrectomy. Only the increased expression of the previously found serum amyloid-alpha (SAA) peak cluster could be validated in a similar RCC patient subset in both our populations in two independent analyses. It was seen both in early- and late-stage disease and in pre- and postsurgery samples. These results were also confirmed by ELISA. Other previously identified biomarker candidates (mass-to-charge ratio's (m/z) 3900, 4107, 4153, 5352 and 5987) proved difficult to reproduce upon duplicate analysis. Modification of the analytical protocol for these markers resulted in their detection, but we did not achieve satisfactory classification of patients and controls with these alleged biomarkers in any of our two sample sets. Instead, two new peaks (m/z 4289 and 8151) were identified with better performance (sensitivity and specificity approximately 65-90%) for separating patients from controls in the first sample set. Concluding, only the SAA peak cluster was validated as a robust RCC biomarker candidate, which is present in a specific subset of these patients, regardless of disease stage or nephrectomy status. In addition, two new peaks were seen which might prove useful as biomarkers, provided these are validated in new populations.