A guide to writing systematic reviews of rare disease treatments to generate FAIR-compliant datasets: building a Treatabolome
Background Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients an...
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| Published in | Orphanet journal of rare diseases Vol. 15; no. 1; pp. 206 - 11 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
12.08.2020
BioMed Central Ltd BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1750-1172 1750-1172 |
| DOI | 10.1186/s13023-020-01493-7 |
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| Abstract | Background
Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases’ patients and their families.
Aims
This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases’ treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments (“Treatabolome”) at gene and variant levels as part of the H2020 research project Solve-RD.
Results
Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence.
Conclusions
This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases’ treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. |
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| AbstractList | Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases' patients and their families. This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases' treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments ("Treatabolome") at gene and variant levels as part of the H2020 research project Solve-RD. Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence. This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases' treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. Abstract Background Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases’ patients and their families. Aims This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases’ treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments (“Treatabolome”) at gene and variant levels as part of the H2020 research project Solve-RD. Results Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence. Conclusions This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases’ treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. Background Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases' patients and their families. Aims This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases' treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments ("Treatabolome") at gene and variant levels as part of the H2020 research project Solve-RD. Results Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence. Conclusions This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases' treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. Keywords: Rare diseases, Systematic literature reviews, Treatment knowledge-base Background Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases’ patients and their families. Aims This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases’ treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments (“Treatabolome”) at gene and variant levels as part of the H2020 research project Solve-RD. Results Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence. Conclusions This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases’ treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases' patients and their families.BACKGROUNDRare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases' patients and their families.This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases' treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments ("Treatabolome") at gene and variant levels as part of the H2020 research project Solve-RD.AIMSThis paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases' treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments ("Treatabolome") at gene and variant levels as part of the H2020 research project Solve-RD.Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence.RESULTSEach systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence.This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases' treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data.CONCLUSIONSThis paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases' treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. Background: Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases' patients and their families.Aims: This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases' treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments ("Treatabolome") at gene and variant levels as part of the H2020 research project Solve-RD.Results: Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence.Conclusions: This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases' treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity translates into a delayed diagnosis, with 25% of patients waiting 5 to 30 years for one. It is essential to raise awareness of patients and clinicians of existing gene and variant-specific therapeutics at the time of diagnosis to avoid that treatment delays add up to the diagnostic odyssey of rare diseases' patients and their families. This paper aims to provide guidance and give detailed instructions on how to write homogeneous systematic reviews of rare diseases' treatments in a manner that allows the capture of the results in a computer-accessible form. The published results need to comply with the FAIR guiding principles for scientific data management and stewardship to facilitate the extraction of datasets that are easily transposable into machine-actionable information. The ultimate purpose is the creation of a database of rare disease treatments ("Treatabolome") at gene and variant levels as part of the H2020 research project Solve-RD. Each systematic review follows a written protocol to address one or more rare diseases in which the authors are experts. The bibliographic search strategy requires detailed documentation to allow its replication. Data capture forms should be built to facilitate the filling of a data capture spreadsheet and to record the application of the inclusion and exclusion criteria to each search result. A PRISMA flowchart is required to provide an overview of the processes of search and selection of papers. A separate table condenses the data collected during the Systematic Review, appraised according to their level of evidence. This paper provides a template that includes the instructions for writing FAIR-compliant systematic reviews of rare diseases' treatments that enables the assembly of a Treatabolome database that complement existing diagnostic and management support tools with treatment awareness data. |
| ArticleNumber | 206 |
| Audience | Academic |
| Author | Lohmann, Katja Evangelista, Teresinha Macaya, Alfons Desaphy, Jean-François Laurie, Steven Bros-Facer, Virginie Horvath, Rita Gómez-Andrés, David Riess, Olaf Synofzik, Matthis Bonne, Gisèle Corvo, Alberto Graessner, Holm Robinson, Peter Atalaia, Antonio Yaou, Rabah Ben Beltran, Sergi Hernandez-Ferrer, Carles Jennings, Matthew J. Lochmuller, Hanns Lochmuller, Angela Fontaine, Bertrand Zurek, Birte Gumus, Gulcin Carmody, Leigh Matalonga, Leslie Reinhard, Carola Chinnery, Patrick Piscia, Davide Ratnaike, Thiloka Schon, Katherine Thompson, Rachel |
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Pitié-Salpêtrière Paris – sequence: 2 givenname: Rachel surname: Thompson fullname: Thompson, Rachel organization: Children’s Hospital of Eastern Ontario Research Institute – sequence: 3 givenname: Alberto surname: Corvo fullname: Corvo, Alberto organization: CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST) – sequence: 4 givenname: Leigh surname: Carmody fullname: Carmody, Leigh organization: The Jackson Laboratory For Genomic Medicine – sequence: 5 givenname: Davide surname: Piscia fullname: Piscia, Davide organization: CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST) – sequence: 6 givenname: Leslie surname: Matalonga fullname: Matalonga, Leslie organization: CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST) – sequence: 7 givenname: Alfons surname: Macaya fullname: Macaya, Alfons organization: Paediatric Neurology, Vall d’Hebron University Hospital and VHIR (Euro-NMD, ERN-RND) – sequence: 8 givenname: Angela surname: Lochmuller fullname: Lochmuller, Angela organization: Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus – sequence: 9 givenname: Bertrand surname: Fontaine fullname: Fontaine, Bertrand organization: Sorbonne Universite - Inserm UMRS 974, Center of Research in Myology, Institut de Myologie, G.H. Pitié-Salpêtrière Paris – sequence: 10 givenname: Birte surname: Zurek fullname: Zurek, Birte organization: Institute of Medical Genetics and Applied Genomics, University of Tuebingen – sequence: 11 givenname: Carles surname: Hernandez-Ferrer fullname: Hernandez-Ferrer, Carles organization: CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST) – sequence: 12 givenname: Carola surname: Reinhard fullname: Reinhard, Carola organization: Institute of Medical Genetics and Applied Genomics, University of Tuebingen – sequence: 13 givenname: David surname: Gómez-Andrés fullname: Gómez-Andrés, David organization: Paediatric Neurology, Vall d’Hebron University Hospital and VHIR (Euro-NMD, ERN-RND) – sequence: 14 givenname: Jean-François surname: Desaphy fullname: Desaphy, Jean-François organization: Department of Biomedical Sciences and Human Oncology, School of Medicine, University of Bari Aldo Moro – sequence: 15 givenname: Katherine surname: Schon fullname: Schon, Katherine organization: Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus – sequence: 16 givenname: Katja surname: Lohmann fullname: Lohmann, Katja organization: Institute of Neurogenetics, University of Lübeck – sequence: 17 givenname: Matthew J. surname: Jennings fullname: Jennings, Matthew J. organization: Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus – sequence: 18 givenname: Matthis surname: Synofzik fullname: Synofzik, Matthis organization: Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, German Center for Neurodegenerative Diseases (DZNE), University of Tübingen – sequence: 19 givenname: Olaf surname: Riess fullname: Riess, Olaf organization: Institute of Medical Genetics and Applied Genomics, University of Tuebingen – sequence: 20 givenname: Rabah Ben surname: Yaou fullname: Yaou, Rabah Ben organization: Sorbonne Universite - Inserm UMRS 974, Center of Research in Myology, Institut de Myologie, G.H. Pitié-Salpêtrière Paris – sequence: 21 givenname: Teresinha surname: Evangelista fullname: Evangelista, Teresinha organization: Unité de Morphologie Neuromusculaire, Institut de Myologie, GHU Pitié-Salpêtrière, Sorbonne Université, AP-HP, INSERM, Centre de référence Des Maladies Neuromusculaires Nord/Est – sequence: 22 givenname: Thiloka surname: Ratnaike fullname: Ratnaike, Thiloka organization: Department of Paediatrics, Cambridge University Hospitals NHS Foundation Trust, Department of Clinical Neurosciences, University of Cambridge – sequence: 23 givenname: Virginie surname: Bros-Facer fullname: Bros-Facer, Virginie organization: EURORDIS – Rare Diseases Europe – sequence: 24 givenname: Gulcin surname: Gumus fullname: Gumus, Gulcin organization: EURORDIS – Rare Diseases Europe – sequence: 25 givenname: Rita surname: Horvath fullname: Horvath, Rita organization: Department of Clinical Neurosciences, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus – sequence: 26 givenname: Patrick surname: Chinnery fullname: Chinnery, Patrick organization: Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge and MRC Mitochondrial Biology Unit, Cambridge Biomedical Campus – sequence: 27 givenname: Steven surname: Laurie fullname: Laurie, Steven organization: CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST) – sequence: 28 givenname: Holm surname: Graessner fullname: Graessner, Holm organization: Institute of Medical Genetics and Applied Genomics, University of Tuebingen – sequence: 29 givenname: Peter surname: Robinson fullname: Robinson, Peter organization: The Jackson Laboratory For Genomic Medicine – sequence: 30 givenname: Hanns surname: Lochmuller fullname: Lochmuller, Hanns organization: Children’s Hospital of Eastern Ontario Research Institute, CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Department of Neuropediatrics and Muscle Disorders, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Division of Neurology, Department of Medicine, The Ottawa Hospital, Brain and Mind Research Institute, University of Ottawa – sequence: 31 givenname: Sergi surname: Beltran fullname: Beltran, Sergi organization: CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST) – sequence: 32 givenname: Gisèle surname: Bonne fullname: Bonne, Gisèle organization: Sorbonne Universite - Inserm UMRS 974, Center of Research in Myology, Institut de Myologie, G.H. 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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32787960$$D View this record in MEDLINE/PubMed https://hal.sorbonne-universite.fr/hal-02935405$$DView record in HAL |
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| Keywords | Rare diseases Treatment knowledge-base Systematic literature reviews |
| Language | English |
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| References | CP Austin (1493_CR7) 2018; 11 Swan_UK W, Eurordis, Rare_Voices_Australia, CORD, NORD, ASRID (1493_CR4) 2016 CRD (1493_CR12) 2019 R Thompson (1493_CR6) 2019; 3 NT Southall (1493_CR8) 2019; 14 S Nguengang Wakap (1493_CR2) 2019; 28 Cochrane_Collaboration. Collaboration C (1493_CR20) 2011 AB Haidich (1493_CR18) 2010; 14 AR Jadad (1493_CR16) 1996; 17 IJ Marshall (1493_CR21) 2019; 8 AJ van Altena (1493_CR22) 2019; 10 1493_CR17 L Kempf (1493_CR3) 2018; 176 EU (1493_CR9) 2017 UoSC (1493_CR13) 2019 S Pletscher-Frankild (1493_CR10) 2015; 74 KM Boycott (1493_CR5) 2020; 106 M Borenstein (1493_CR19) 2009 University_of_Tasmania (1493_CR14) 2019 PRISMA (1493_CR15) 2019 HJS Dawkins (1493_CR1) 2018; 11 MD Wilkinson (1493_CR11) 2016; 3 33752678 - Orphanet J Rare Dis. 2021 Mar 22;16(1):145. doi: 10.1186/s13023-021-01777-6. |
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Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their... Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their rarity... Background Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their... Background: Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined. Their... Abstract Background Rare diseases are individually rare but globally affect around 6% of the population, and in over 70% of cases are genetically determined.... |
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| Title | A guide to writing systematic reviews of rare disease treatments to generate FAIR-compliant datasets: building a Treatabolome |
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