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Record W4312095328 · doi:10.1210/clinem/dgac621

Treatment of Hypercalcemia of Malignancy in Adults: An Endocrine Society Clinical Practice Guideline

2022· review· en· W4312095328 on OpenAlexafffund
Ghada El‐Hajj Fuleihan, Gregory A. Clines, Mimi I. Hu, Claudio Marcocci, M. Hassan Murad, Thomas Piggott, Catherine Van Poznak, Joy Y. Wu, Matthew T. Drake

Bibliographic record

VenueThe Journal of Clinical Endocrinology & Metabolism · 2022
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsMcMaster UniversityImpactQueen's University
FundersMcMaster UniversityAmerican Society of Clinical OncologyEndocrine Society
KeywordsMedicineGuidelineIntensive care medicineGrading (engineering)MalignancyMultidisciplinary approachClinical PracticePediatricsInternal medicineFamily medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Hypercalcemia of malignancy (HCM) is the most common metabolic complication of malignancies, but its incidence may be declining due to potent chemotherapeutic agents. The high mortality associated with HCM has declined markedly due to the introduction of increasingly effective chemotherapeutic drugs. Despite the widespread availability of efficacious medications to treat HCM, evidence-based recommendations to manage this debilitating condition are lacking. OBJECTIVE: To develop guidelines for the treatment of adults with HCM. METHODS: A multidisciplinary panel of clinical experts, together with experts in systematic literature review, identified and prioritized 8 clinical questions related to the treatment of HCM in adult patients. The systematic reviews (SRs) queried electronic databases for studies relevant to the selected questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations. An independent SR was conducted in parallel to assess patients' and physicians' values and preferences, costs, resources needed, acceptability, feasibility, equity, and other domains relevant to the Evidence-to-Decision framework as well as to enable judgements and recommendations. RESULTS: The panel recommends (strong recommendation) in adults with HCM treatment with denosumab (Dmab) or an intravenous (IV) bisphosphonate (BP). The following recommendations were based on low certainty of the evidence. The panel suggests (conditional recommendation) (1) in adults with HCM, the use of Dmab rather than an IV BP; (2) in adults with severe HCM, a combination of calcitonin and an IV BP or Dmab therapy as initial treatment; and (3) in adults with refractory/recurrent HCM despite treatment with BP, the use of Dmab. The panel suggests (conditional recommendation) the addition of an IV BP or Dmab in adult patients with hypercalcemia due to tumors associated with high calcitriol levels who are already receiving glucocorticoid therapy but continue to have severe or symptomatic HCM. The panel suggests (conditional recommendation) in adult patients with hypercalcemia due to parathyroid carcinoma, treatment with either a calcimimetic or an antiresorptive (IV BP or Dmab). The panel judges the treatments as probably accessible and feasible for most recommendations but noted variability in costs, resources required, and their impact on equity. CONCLUSIONS: The panel's recommendations are based on currently available evidence considering the most important outcomes in HCM to patients and key stakeholders. Treatment of the primary malignancy is instrumental for controlling hypercalcemia and preventing its recurrence. The recommendations provide a framework for the medical management of adults with HCM and incorporate important decisional and contextual factors. The guidelines underscore current knowledge gaps that can be used to establish future research agendas.

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)0.010
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0040.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0040.002

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 head0.181
GPT teacher head0.527
Teacher spread0.346 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations100
Published2022
Admission routes2
Has abstractyes

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