27 research outputs found

    Patient-reported outcomes during repetitive oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy for isolated unresectable colorectal peritoneal metastases in a multicenter, single-arm, phase 2 trial (CRC-PIPAC)

    Get PDF
    BACKGROUND: CRC-PIPAC prospectively assessed repetitive oxaliplatin-based pressurized intraperitoneal aerosol chemotherapy (PIPAC-OX) as a palliative monotherapy (i.e., without concomitant systemic therapy in between subsequent procedures) for unresectable colorectal peritoneal metastases (CPM). The present study explored patient-reported outcomes (PROs) during trial treatment. METHODS: In this single-arm phase 2 trial in two tertiary centers, patients with isolated unresectable CPM received 6-weekly PIPAC-OX (92 mg/m(2)). PROs (calculated from EQ-5D-5L, and EORTC QLQ-C30 and QLQ-CR29) were compared between baseline and 1 and 4 weeks after the first three procedures using linear mixed modeling with determination of clinical relevance (Cohen’s D ≥ 0.50) of statistically significant differences. RESULTS: Twenty patients underwent 59 procedures (median 3 [range 1–6]). Several PROs solely worsened 1 week after the first procedure (index value − 0.10, p < 0.001; physical functioning − 20, p < 0.001; role functioning − 27, p < 0.001; social functioning − 18, p < 0.001; C30 summary score − 16, p < 0.001; appetite loss + 15, p = 0.007; diarrhea + 15, p = 0.002; urinary frequency + 13, p = 0.004; flatulence + 13, p = 0.001). These PROs returned to baseline at subsequent time points. Other PROs worsened 1 week after the first procedure (fatigue + 23, p < 0.001; pain + 29, p < 0.001; abdominal pain + 32, p < 0.001), second procedure (fatigue + 20, p < 0.001; pain + 21, p < 0.001; abdominal pain + 20, p = 0.002), and third procedure (pain + 22, p < 0.001; abdominal pain + 22, p = 0.002). Except for appetite loss, all changes were clinically relevant. All analyzed PROs returned to baseline 4 weeks after the third procedure. CONCLUSIONS: Patients receiving repetitive PIPAC-OX monotherapy for unresectable CPM had clinically relevant but reversible worsening of several PROs, mainly 1 week after the first procedure. TRIAL REGISTRATION: Clinicaltrials.gov: NCT03246321; Netherlands trial register: NL6426. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00464-021-08802-6

    Molecular diagnosis of Burkitt\u27s lymphoma.

    Get PDF
    BACKGROUND: The distinction between Burkitt\u27s lymphoma and diffuse large-B-cell lymphoma is crucial because these two types of lymphoma require different treatments. We examined whether gene-expression profiling could reliably distinguish Burkitt\u27s lymphoma from diffuse large-B-cell lymphoma. METHODS: Tumor-biopsy specimens from 303 patients with aggressive lymphomas were profiled for gene expression and were also classified according to morphology, immunohistochemistry, and detection of the t(8;14) c-myc translocation. RESULTS: A classifier based on gene expression correctly identified all 25 pathologically verified cases of classic Burkitt\u27s lymphoma. Burkitt\u27s lymphoma was readily distinguished from diffuse large-B-cell lymphoma by the high level of expression of c-myc target genes, the expression of a subgroup of germinal-center B-cell genes, and the low level of expression of major-histocompatibility-complex class I genes and nuclear factor-kappaB target genes. Eight specimens with a pathological diagnosis of diffuse large-B-cell lymphoma had the typical gene-expression profile of Burkitt\u27s lymphoma, suggesting they represent cases of Burkitt\u27s lymphoma that are difficult to diagnose by current methods. Among 28 of the patients with a molecular diagnosis of Burkitt\u27s lymphoma, the overall survival was superior among those who had received intensive chemotherapy regimens instead of lower-dose regimens. CONCLUSIONS: Gene-expression profiling is an accurate, quantitative method for distinguishing Burkitt\u27s lymphoma from diffuse large-B-cell lymphoma

    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

    Get PDF
    Background Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach 1398pooledhealthspendingpercapita(US1398 pooled health spending per capita (US adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC

    Mass Spectrometric Characterization of Protein Adducts of Multiple P450-Dependent Reactive Intermediates of Diclofenac to Human Glutathione‑<i>S</i>‑transferase P1‑1

    No full text
    Use of the nonsteroidal anti-inflammatory drug diclofenac (DF) is associated with serious idiosyncratic hepatotoxicity. Covalent binding of reactive intermediates of DF to proteins is considered to initiate the process leading to this severe side-effect. The aim of this study was to characterize the nature of covalent protein modifications by reactive metabolites of DF which result from bioactivation by cytochrome P450. DF and its major monohydroxylated metabolites 4′-hydroxydiclofenac (4′-OH-DF) and 5-hydroxydiclofenac (5-OH-DF) were bioactivated using a highly active P450 BM3 mutant (CYP102A1M11H) in the presence of the model target protein human glutathione-<i>S</i>-transferase P1-1 (hGST P1-1). Protein-adducts were subsequently identified by LC-MS/MS analysis of tryptic digests of hGST P1-1. In total, 10 different peptide adducts were observed which result from modifications of Cys-47 and Cys-14 of hGST P1-1. The majority of the protein thiol modifications appeared to be derived from 5-OH-DF, which produced seven different peptide adducts with mass increments of 289.0, 309.0, and 339.0 Da. Remarkably, no peptide adducts were observed upon the bioactivation of 4′-OH-DF. Incubations of P450 BM3 with DF also showed the peptide adducts derived from 5-OH-DF and peptide adducts that are not derived from quinone imine. A peptide adduct with a mass increment of 249.0 Da most likely results from the <i>o</i>-imine methide formed by oxidative decarboxylation of DF. In addition, a peptide adduct was observed with a mass increment of 259.0 Da, which corresponds to the substitution of one of the chlorine atoms of DF by protein thiol. A corresponding GSH-conjugate with a similar mass increment was only observed if incubations of DF with P450 and GSH were supplemented by human GST P1-1. The results of this study not only confirm the importance of 5-OH-DF in covalent protein-binding but also suggest that the nature of protein adduction is not necessarily reflected by chemical conjugation with GSH

    Reporting Weight Loss 2021: Position Statement of the Dutch Society for Metabolic and Bariatric Surgery (DSMBS)

    No full text
    Prevailing recommendations on reporting weight loss after bariatric and metabolic surgery are not evidence-based. They promote the outcome metric percentage excess weight loss (%EWL), sometimes indicated as percentage excess body mass index loss (%EBMIL). Many studies proved that this popular outcome measure, in contrast to other weight loss metrics, is inaccurate and error-sensitive when comparing weight loss within and between studies. It is inappropriate for assessing poor weight loss response and weight regain as well. The percentage (total) weight loss metric is the best alternative. The Dutch Society for Metabolic and Bariatric Surgery (DSMBS) recommends to stop using the %EWL (or %EBMIL) metric as primary outcome measure in all cases and calls on the International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO) to propagate this evidence-based recommendation. Graphical Abstract: [Figure not available: see fulltext.

    Glutathione-S-transferase pi as a model protein for the characterisation of chemically reactive metabolites

    No full text
    Chemically reactive metabolites (CRMs) are thought to be responsible for a number of adverse drug reactions through modification of critical proteins. Methods that defined the chemistry of protein modification at an early stage would provide invaluable tools for drug safety assessment. Here, human GST pi (GSTP) was exploited as a model target protein to determine the chemical, biochemical and functional consequences of exposure to the hepatotoxic CRM of paracetamol (APAP), N-acetyl-p-benzoquinoneimine (NAPQI). Site-specific, dose-dependent modification of Cys47 in native and His-tagged GSTP was revealed by MS, and correlated with inhibition of glutathione (GSH) conjugating activity. In addition, the adaptation of iTRAQ labelling technology to define precisely the quantitative relationship between covalent modification and protein function is described. Multiple reaction monitoring (MRM)-MS of GSTP allowed high sensitivity detection of modified peptides at physiological levels of exposure. Finally, a bioengineered mutant cytochrome P450 with a broad spectrum of substrate specificities was used in an in vitro reaction system to bioactivate APAP: in this model, GSTP trapped the CRM and exhibited both reduced enzyme activity and site-specific modification of the protein. These studies provide the foundation for the development of novel test systems to predict the toxicological potential of CRMs produced by new therapeutic agents

    Systemic Pharmacokinetics of Oxaliplatin After Intraperitoneal Administration by Electrostatic Pressurized Intraperitoneal Aerosol Chemotherapy (ePIPAC) in Patients with Unresectable Colorectal Peritoneal Metastases in the CRC-PIPAC Trial

    No full text
    Background Electrostatic pressurized intraperitoneal aerosol chemotherapy (ePIPAC) is a palliative treatment for unresectable peritoneal metastases from various primary cancers. However, little is known about the systemic pharmacokinetics of oxaliplatin after ePIPAC. Methods Twenty patients with unresectable colorectal peritoneal metastases were treated with repetitive ePIPAC monotherapy with oxaliplatin (92 mg/m(2)) and a simultaneous intravenous bolus of leucovorin (20 mg/m(2)) and 5-fluorouracil (400 mg/m(2)). Samples were collected during each ePIPAC: whole blood att = 0,t = 5,t = 10,t = 20,t = 30,t = 60,t = 120,t = 240,t = 360 andt = 1080 min for plasma and plasma ultrafiltrate concentrations; urine att = 0,t = 1,t = 3,t = 5 andt = 7 days. Samples were analyzed using atomic absorption spectrometry. Pharmacokinetics were analyzed using nonlinear mixed-effects modeling. Results Four patients received one ePIPAC, three patients received two ePIPAC, and thirteen patients received >= 3 ePIPAC. The population pharmacokinetic models adequately described the pharmacokinetics of oxaliplatin after ePIPAC. The plasma ultrafiltrateC(max)of oxaliplatin reached 1.36-1.90 mu g/mL after 30 min with an AUC(0-24 h)of 9.6-11.7 mu g/mL * h. The plasmaC(max)reached 2.67-3.28 mu g/mL after 90 min with an AUC(0-24 h)of 49.0-59.5 mu g/mL * h. The absorption rate constant (Ka) was 1.13/h. Urine concentrations of oxaliplatin rapidly decreased to less than 3.60 mu g/mL in 90% of the samples at day 7. Discussion Systemic exposure to oxaliplatin after ePIPAC seemed comparable to that after systemic chemotherapy, as described in other literature. Since this is an indirect comparison, future research should focus on the direct comparison between the systemic exposure to oxaliplatin after ePIPAC and after systemic chemotherapy
    corecore