MétaCan
Menu
Back to cohort
Record W3177296884 · doi:10.1186/s13023-021-01899-x

Direct and indirect costs and cost-driving factors of Tuberous sclerosis complex in children, adolescents, and caregivers: a multicenter cohort study

2021· article· en· W3177296884 on OpenAlexaff
Janina Grau, Johann Philipp Zöllner, Susanne Schubert‐Bast, Gerhard Kurlemann, Christoph Hertzberg, Adelheid Wiemer‐Kruel, Thomas Bast, Astrid Bertsche, U Bettendorf, Barbara Fiedler, Andreas Hahn, Hans Hartmann, Frauke Hornemann, Ilka Immisch, Julia Jacobs, Matthias Kieslich, Karl Martin Klein, Kerstin Alexandra Klotz, Gerhard Kluger, Markus Knuf, Klaus Marquard, Sascha Meyer, Hiltrud Muhle, Karen Müller‐Schlüter, Anna H. Noda, Susanne Ruf, Matthias Sauter, Jan-Ulrich Schlump, Steffen Syrbe, Charlotte Thiels, Regina Trollmann, Bernd Wilken, Laurent M. Willems, Felix Rosenow, Adam Strzelczyk

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2021
Typearticle
Languageen
FieldMedicine
TopicTuberous Sclerosis Complex Research
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsTuberous sclerosisMedicineIndirect costsTSC1CohortPediatricsConfidence intervalRetrospective cohort studyCohort studyInternal medicinePsychiatryPI3K/AKT/mTOR pathway

Abstract

fetched live from OpenAlex

BACKGROUND: Tuberous sclerosis complex (TSC), a multisystem genetic disorder, affects many organs and systems, characterized by benign growths. This German multicenter study estimated the disease-specific costs and cost-driving factors associated with various organ manifestations in TSC patients. METHODS: A validated, three-month, retrospective questionnaire was administered to assess the sociodemographic and clinical characteristics, organ manifestations, direct, indirect, out-of-pocket, and nursing care-level costs, completed by caregivers of patients with TSC throughout Germany. RESULTS: The caregivers of 184 patients (mean age 9.8 ± 5.3 years, range 0.7-21.8 years) submitted questionnaires. The reported TSC disease manifestations included epilepsy (92%), skin disorders (86%), structural brain disorders (83%), heart and circulatory system disorders (67%), kidney and urinary tract disorders (53%), and psychiatric disorders (51%). Genetic variations in TSC2 were reported in 46% of patients, whereas 14% were reported in TSC1. Mean total direct health care costs were EUR 4949 [95% confidence interval (95% CI) EUR 4088-5863, median EUR 2062] per patient over three months. Medication costs represented the largest direct cost category (54% of total direct costs, mean EUR 2658), with mechanistic target of rapamycin (mTOR) inhibitors representing the largest share (47%, EUR 2309). The cost of anti-seizure drugs (ASDs) accounted for a mean of only EUR 260 (5%). Inpatient costs (21%, EUR 1027) and ancillary therapy costs (8%, EUR 407) were also important direct cost components. The mean nursing care-level costs were EUR 1163 (95% CI EUR 1027-1314, median EUR 1635) over three months. Total indirect costs totaled a mean of EUR 2813 (95% CI EUR 2221-3394, median EUR 215) for mothers and EUR 372 (95% CI EUR 193-586, median EUR 0) for fathers. Multiple regression analyses revealed polytherapy with two or more ASDs and the use of mTOR inhibitors as independent cost-driving factors of total direct costs. Disability and psychiatric disease were independent cost-driving factors for total indirect costs as well as for nursing care-level costs. CONCLUSIONS: This study revealed substantial direct (including medication), nursing care-level, and indirect costs associated with TSC over three months, highlighting the spectrum of organ manifestations and their treatment needs in the German healthcare setting. TRIAL REGISTRATION: DRKS, DRKS00016045. Registered 01 March 2019, http://www.drks.de/DRKS00016045.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.285
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueOrphanet Journal of Rare DiseasesSame topicTuberous Sclerosis Complex ResearchFrench-language works237,207