Studying de-implementation in health: an analysis of funded research grants

Background

Studying de-implementation—defined herein as reducing or stopping the use of a health service or practice provided to patients by healthcare practitioners and systems—has gained traction in recent years. De-implementing ineffective, unproven, harmful, overused, inappropriate, and/or low-value health services and practices is important for mitigating patient harm, improving processes of care, and reducing healthcare costs. A better understanding of the state-of-the-science is needed to guide future objectives and funding initiatives. To this end, we characterized de-implementation research grants funded by the United States (US) National Institutes of Health (NIH) and the Agency for Healthcare Research and Quality (AHRQ).

Methods

We used systematic methods to search, identify, and describe de-implementation research grants funded across all 27 NIH Institutes and Centers (ICs) and AHRQ from fiscal year 2000 through 2017. Eleven key terms and three funding opportunity announcements were used to search for research grants in the NIH Query, View and Report (QVR) system. Two coders identified eligible grants based on inclusion/exclusion criteria. A codebook was developed, pilot tested, and revised before coding the full grant applications of the final sample.

Results

A total of 1277 grants were identified through the QVR system; 542 remained after removing duplicates. After the multistep eligibility assessment and review process, 20 grant applications were coded. Many grants were funded by NIH (n?=?15), with fewer funded by AHRQ, and a majority were funded between fiscal years 2015 and 2016 (n?=?11). Grant proposals focused on de-implementing a range of health services and practices (e.g., medications, therapies, screening tests) across various health areas (e.g., cancer, cardiovascular disease) and delivery settings (e.g., hospitals, nursing homes, schools). Grants proposed to use a variety of study designs and research methods (e.g., experimental, observational, mixed methods) to accomplish study aims.

Conclusions

Based on the systematic portfolio analysis of NIH- and AHRQ-funded research grants over the past 17 years, relatively few have focused on studying the de-implementation of ineffective, unproven, harmful, overused, inappropriate, and/or low-value health services and practices provided to patients by healthcare practitioners and systems. Strategies for raising the profile and growing the field of research on de-implementation are discussed.

     

Accuracy of serum luteinizing hormone and serum testosterone measurements to assess the efficacy of medical castration in prostate cancer patients

Background

Luteinizing hormone-releasing hormone (LH-RH) agonists are the standard for androgen deprivation therapy (ADT) in prostate cancer (PCa) patients. Current guidelines recommend serum testosterone measurement to assess the efficacy of ADT and to define castration resistance. However, serum testosterone does not reflect the exclusive effect of castration due to its extratesticular production. The aim of this study is to analyze if serum LH reflects better than serum testosterone the activity of LH-RH agonists.

Methods

Serum LH and serum testosterone were measured with chemiluminescent immunoassay (CLIA) in a cohort study of 1091 participants: 488 PCa patients “on LH-RH agonists”, 303 “off LH-RH agonist” in whom LH-RH agonists were withdrawn, and 350 men with PCa suspicion “no LH-RH agonist” who never received LH-RH agonists. In a validation cohort of 147 PCa patients, 124 on “LH-RH agonists” and 19 “off LH-RH agonists”, serum testosterone was also measured with liquid chromatography and tandem mass spectrometry (LC MSMS).

Results

The area under the curve (AUC) to distinguish patients “on versus off LH-RH agonists” was 0.997 for serum LH and 0.740 for serum testosterone, P < 0.001. The 97.5 percentile of serum LH in patients “on LH-RH agonists” was 0.97 U/L, been the most efficient threshold 1.1 U/L. The AUCs for serum LH, testosterone measured with CLIA and with LC MSMS, in the validation cohort, were respectively 1.000, 0.646 and 0.814, P < 0.001. The efficacy to distinguish patients “on versus off LH-RH agonists” was 98.6%, 78.3%, and 89.5% respectively, using 1.1 U/L as threshold for serum LH and 50 ng/dL for serum testosterone regardless the method.

Conclusions

Serum LH is more accurate than serum testosterone regardless the method, to distinguish patients “on versus off LH-RH agonists”. The castrate level of serum LH is 1.1 U/l. These findings suggest that assessment of LH-RH agonist efficacy and castration resistance definition should be reviewed.

     

A change from gonadotropin releasing hormone antagonist to gonadotropin releasing hormone agonist therapy does not affect the oncological outcomes in hormone sensitive prostate cancer

Background

The aim of our retrospective study was to evaluate the 5-year survival and time to castration resistant prostate cancer in patients with hormone sensitive prostate cancer treated with the gonadotropin releasing hormone antagonist, degarelix. Another aim was to evaluate the effects of changing the treatment from degarelix to a gonadotropin releasing hormone agonist after achieving stable disease control, on the clinical and oncological outcomes.

Results

Our analysis was based on the data of 108 patients with prostate cancer who were treated with degarelix. Of these, the treatment was changed from degarelix to a gonadotropin releasing hormone agonist in 57 patients (changed group), and the treatment with degarelix was continued in the other 51 (continued group). The overall 5-year survival was statistically superior in the changed (96.6%) group than that in the continued (74.1%) group (p?=?0.006). The 5-year cancer-specific survival was also superior in the changed (100%) group than that in the continued (84.6%) group (p?=?0.027). The average time to castration resistant prostate cancer was comparable in both the changed (43.3 months) and continued (35.2 months) groups (p?=?0.117). Lower serum levels of prostate specific antigen and alkaline phosphatase were maintained after changing the therapy from degarelix to a gonadotropin releasing hormone agonist.

Conclusions

Degarelix is effective in the treatment of prostate cancer. Degarelix therapy can also be safely changed to a gonadotropin releasing hormone agonist without any adverse clinical or oncological effects.

     

Automatic recognition of topic-classified relations between prostate cancer and genes using MEDLINE abstracts

Background

Automatic recognition of relations between a specific disease term and its relevant genes or protein terms is an important practice of bioinformatics. Considering the utility of the results of this approach, we identified prostate cancer and gene terms with the ID tags of public biomedical databases. Moreover, considering that genetics experts will use our results, we classified them based on six topics that can be used to analyze the type of prostate cancers, genes, and their relations.

Methods

We developed a maximum entropy-based named entity recognizer and a relation recognizer and applied them to a corpus-based approach. We collected prostate cancer-related abstracts from MEDLINE, and constructed an annotated corpus of gene and prostate cancer relations based on six topics by biologists. We used it to train the maximum entropy-based named entity recognizer and relation recognizer.

Results

Topic-classified relation recognition achieved 92.1% precision for the relation (an increase of 11.0% from that obtained in a baseline experiment). For all topics, the precision was between 67.6 and 88.1%.

Conclusion

A series of experimental results revealed two important findings: a carefully designed relation recognition system using named entity recognition can improve the performance of relation recognition, and topic-classified relation recognition can be effectively addressed through a corpus-based approach using manual annotation and machine learning techniques.

     

A streamlined method for analysing genome-wide DNA methylation patterns from low amounts of FFPE DNA

Background

Formalin fixed paraffin embedded (FFPE) tumor samples are a major source of DNA from patients in cancer research. However, FFPE is a challenging material to work with due to macromolecular fragmentation and nucleic acid crosslinking. FFPE tissue particularly possesses challenges for methylation analysis and for preparing sequencing-based libraries relying on bisulfite conversion. Successful bisulfite conversion is a key requirement for sequencing-based methylation analysis.

Methods

Here we describe a complete and streamlined workflow for preparing next generation sequencing libraries for methylation analysis from FFPE tissues. This includes, counting cells from FFPE blocks and extracting DNA from FFPE slides, testing bisulfite conversion efficiency with a polymerase chain reaction (PCR) based test, preparing reduced representation bisulfite sequencing libraries and massively parallel sequencing.

Results

The main features and advantages of this protocol are:

• An optimized method for extracting good quality DNA from FFPE tissues.
• An efficient bisulfite conversion and next generation sequencing library preparation protocol that uses 50 ng DNA from FFPE tissue.
• Incorporation of a PCR-based test to assess bisulfite conversion efficiency prior to sequencing.

Conclusions

We provide a complete workflow and an integrated protocol for performing DNA methylation analysis at the genome-scale and we believe this will facilitate clinical epigenetic research that involves the use of FFPE tissue.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Crop metabolomics: from diagnostics to assisted breeding

Background

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.

Aim of Review

We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.

Key Scientific Concepts of Review

Translational metabolomics applied to crop breeding programs.

     

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

Introduction

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.

Objectives

In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.

Methods

Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using ¹H nuclear magnetic resonance (¹H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.

Results

The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.

Conclusion

PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

     

Response of Degarelix treatment in human prostate cancer monitored by HR-MAS <Superscript>1</Superscript>H NMR spectroscopy

Introduction

The androgen receptor (AR) is the master regulator of prostate cancer cell metabolism. Degarelix is a novel gonadotrophin-releasing hormone blocker, used to decrease serum androgen levels in order to treat advanced human prostate cancer. Little is known of the rapid metabolic response of the human prostate cancer tissue samples to the decreased androgen levels.

Objectives

To investigate the metabolic responses in benign and cancerous tissue samples from patients after treatment with Degarelix by using HRMAS ¹H NMR spectroscopy.

Methods

Using non-destructive HR-MAS ¹H NMR spectroscopy we analysed the metabolic changes induced by decreased AR signalling in human prostate cancer tissue samples. Absolute concentrations of the metabolites alanine, lactate, glutamine, glutamate, citrate, choline compounds [t-choline = choline + phosphocholine (PC) + glycerophosphocholine (GPC)], creatine compounds [t-creatine = creatine (Cr) + phosphocreatine (PCr)], taurine, myo-inositol and polyamines were measured in benign prostate tissue samples (n = 10), in prostate cancer specimens from untreated patients (n = 7) and prostate cancer specimens from patients treated with Degarelix (n = 6).

Results

Lactate, alanine and t-choline concentrations were significantly elevated in high-grade prostate cancer samples when compared to benign samples in untreated patients. Decreased androgen levels resulted in significant decreases of lactate and t-choline concentrations in human prostate cancer biopsies.

Conclusions

The reduced concentrations of lactate and t-choline metabolites due to Degarelix could in principle be monitored by in vivo ¹H MRS, which suggests that it would be possible to monitor the effects of physical or chemical castration in patients by that non-invasive method.

     

WNT and NOTCH signaling pathways as activators for epidermal growth factor receptor in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer, with a poor prognosis. Deregulation of WNT and NOTCH signaling pathways is important in ESCC progression, which can be due to either malfunction of their components or crosstalk with other pathways. Therefore, identification of new crosstalk between such pathways may be effective to introduce new strategies for targeted therapy of cancer. A correlation study was performed to assess the probable interaction between growth factor receptors and WNT/NOTCH pathways via the epidermal growth factor receptor (EGFR) and Musashi1 (MSI1), respectively.

Methods

Levels of MSI1/EGFR mRNA expression in tumor tissues from 48 ESCC patients were compared to their corresponding normal tissues using real-time polymerase chain reaction.

Results

There was a significant correlation between EGFR and MSI1 expression (p?=?0.05). Moreover, there was a significant correlation between EGFR/MSI1 expression and grade of tumor differentiation (p?=?0.02).

Conclusion

This study confirms a direct correlation between MSI1 and EGFR and may support the important role of MSI1 in activation of EGFR through NOTCH/WNT pathways in ESCC.

     

The risks of cancer development in systemic lupus erythematosus (SLE) patients: a systematic review and meta-analysis

Background

Although accumulating data have suggested the development of cancer in systemic lupus erythematosus (SLE) patients, these results remain inconsistent. To examine such a putative association, this analysis reports the association between SLE and the risks of 24 cancer types.

Methods

Online databases PubMed, EMBASE, and Web of Science were searched comprehensively for eligible studies, published up to 15 May 2018. Pooled standardized incidence rates (SIRs) with 95% confidence intervals (CIs) were utilized to reveal their associations.

Results

A total of 24 eligible studies were ultimately enrolled. Our results indicated that SLE was associated with increased risk of overall cancers, cancer risk in both genders, non-Hodgkin’s lymphoma, Hodgkin’s lymphoma, leukemia, multiple myeloma, cervix, vagina/vulva, renal, bladder, esophagus, gastric, hepatobiliary, lung, oropharynx, larynx, non-melanoma skin, and thyroid cancers. Additionally, SLE could reduce the risk of prostate cancer and cutaneous melanoma; however, it was not significantly associated with breast, uterus, ovarian, pancreatic, colorectal, or brain cancers.

Conclusions

Our results shed light SLE being correlated with increased risk for 16 involved cancers and decreased risk for prostate cancer and cutaneous melanoma. This comprehensive meta-analysis provides epidemiological evidence supporting the associations between SLE and cancer risk. This evidence could be utilized to drive public policies and to help guide personalized medicine to better manage SLE and reduce associated cancer morbidity and mortality.

     

High salt and fat intake,inflammation, and risk of cancer

Background

Inflammatory conditions are involved in the pathophysiology of cancer. Recent findings have revealed that excessive salt and fat intake is involved in the development of severe inflammatory reactions.

Methods

literature search was performed on various online databases (PubMed, Scopus, and Google Scholar) regarding the roles of high salt and fat intake in the induction of inflammatory reactions and their roles in the etiopathogenesis of cancer.

Results

The results indicate that high salt and fat intake can induce severe inflammatory conditions. However, various inflammatory conditions have been strongly linked to the development of cancer. Hence, high salt and fat intake might be involved in the pathogenesis of cancer progression via putative mechanisms related to inflammatory reactions.

Conclusion

Reducing salt and fat intake may decrease the risk of cancer.

     

How the chemical features of molecules may have addressed the settlement of metabolic steps

Introduction

While the evolutionary adaptation of enzymes to their own substrates is a well assessed and rationalized field, how molecules have been originally selected in order to initiate and assemble convenient metabolic pathways is a fascinating, but still debated argument.

Objectives

Aim of the present study is to give a rationale for the preferential selection of specific molecules to generate metabolic pathways.

Methods

The comparison of structural features of molecules, through an inductive methodological approach, offer a reading key to cautiously propose a determining factor for their metabolic recruitment.

Results

Starting with some commonplaces occurring in the structural representation of relevant carbohydrates, such as glucose, fructose and ribose, arguments are presented in associating stable structural determinants of these molecules and their peculiar occurrence in metabolic pathways.

Conclusions

Among other possible factors, the reliability of the structural asset of a molecule may be relevant or its selection among structurally and, a priori, functionally similar molecules.

     

TarMet: a reactive GUI tool for efficient and confident quantification of MS based targeted metabolic and stable isotope tracer analysis

Introduction

Untargeted and targeted analyses are two classes of metabolic study. Both strategies have been advanced by high resolution mass spectrometers coupled with chromatography, which have the advantages of high mass sensitivity and accuracy. State-of-art methods for mass spectrometric data sets do not always quantify metabolites of interest in a targeted assay efficiently and accurately.

Objectives

TarMet can quantify targeted metabolites as well as their isotopologues through a reactive and user-friendly graphical user interface.

Methods

TarMet accepts vendor-neutral data files (NetCDF, mzXML and mzML) as inputs. Then it extracts ion chromatograms, detects peak position and bounds and confirms the metabolites via the isotope patterns. It can integrate peak areas for all isotopologues automatically.

Results

TarMet detects more isotopologues and quantify them better than state-of-art methods, and it can process isotope tracer assay well.

Conclusion

TarMet is a better tool for targeted metabolic and stable isotope tracer analyses.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

The metabolome 18 years on: a concept comes of age

Background

The term ‘metabolome’ was introduced to the scientific literature in September 1998.

Aim and key scientific concepts of the review

To mark its 18-year-old ‘coming of age’, two of the co-authors of that paper review the genesis of metabolomics, whence it has come and where it may be going.

     

Untargeted and stable isotope-assisted metabolomic analysis of MDA-MB-231 cells under hypoxia

Introduction

Hypoxia commonly occurs in cancers and is highly related with the occurrence, development and metastasis of cancer. Treatment of triple negative breast cancer remains challenge. Knowledge about the metabolic status of triple negative breast cancer cell lines in hypoxia is valuable for the understanding of molecular mechanisms of this tumor subtype to develop effective therapeutics.

Objectives

Comprehensively characterize the metabolic profiles of triple negative breast cancer cell line MDA-MB-231 in normoxia and hypoxia and the pathways involved in metabolic changes in hypoxia.

Methods

Differences in metabolic profiles affected pathways of MDA-MB-231 cells in normoxia and hypoxia were characterized using GC–MS based untargeted and stable isotope assisted metabolomic techniques.

Results

Thirty-three metabolites were significantly changed in hypoxia and nine pathways were involved. Hypoxia increased glycolysis, inhibited TCA cycle, pentose phosphate pathway and pyruvate carboxylation, while increased glutaminolysis in MDA-MB-231 cells.

Conclusion

The current results provide metabolic differences of MDA-MB-231 cells in normoxia and hypoxia conditions as well as the involved metabolic pathways, demonstrating the power of combined use of untargeted and stable isotope-assisted metabolomic methods in comprehensive metabolomic analysis.

     

Best serum biomarker combination for ovarian cancer classification

Background

Screening test using CA-125 is the most common test for detecting ovarian cancer. However, the level of CA-125 is diverse by variable condition other than ovarian cancer. It has led to misdiagnosis of ovarian cancer.

Methods

In this paper, we explore the 16 serum biomarker for finding alternative biomarker combination to reduce misdiagnosis. For experiment, we use the serum samples that contain 101 cancer and 92 healthy samples. We perform two major tasks: Marker selection and Classification. For optimal marker selection, we use genetic algorithm, random forest, T-test and logistic regression. For classification, we compare linear discriminative analysis, K-nearest neighbor and logistic regression.

Results

The final results show that the logistic regression gives high performance for both tasks, and HE4-ELISA, PDGF-AA, Prolactin, TTR is the best biomarker combination for detecting ovarian cancer.

Conclusions

We find the combination which contains TTR and Prolactin gives high performance for cancer detection. Early detection of ovarian cancer can reduce high mortality rates. Finding a combination of multiple biomarkers for diagnostic tests with high sensitivity and specificity is very important.

     

Targeted metabolomic profiling of low and high grade serous epithelial ovarian cancer tissues: a pilot study

Introduction

Epithelial ovarian cancer (EOC) remains the leading cause of death from gynecologic malignancies and has an alarming global fatality rate. Besides the differences in underlying pathogenesis, distinguishing between high grade (HG) and low grade (LG) EOC is imperative for the prediction of disease progression and responsiveness to chemotherapy.

Objectives

The aim of this study was to investigate, the tissue metabolome associated with HG and LG serous epithelial ovarian cancer.

Methods

A combination of one dimensional proton nuclear magnetic resonance (1D H NMR) spectroscopy and targeted mass spectrometry (MS) was employed to profile the tissue metabolome of HG, LG serous EOCs, and controls.

Results

Using partial least squares-discriminant analysis, we observed significant separation between all groups (p?<?0.05) following cross validation. We identified which metabolites were significantly perturbed in each EOC grade as compared with controls and report the biochemical pathways which were perturbed due to the disease. Among these metabolic pathways, ascorbate and aldarate metabolism was identified, for the first time, as being significantly altered in both LG and HG serous cancers. Further, we have identified potential biomarkers of EOC and generated predictive algorithms with AUC (CI)?=?0.940 and 0.929 for HG and LG, respectively.

Conclusion

These previously unreported biochemical changes provide a framework for future metabolomic studies for the development of EOC biomarkers. Finally, pharmacologic targeting of the key metabolic pathways identified herein could lead to novel and effective treatments of EOC.