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Record W2030471933 · doi:10.2217/cer.12.72

Adverse events across generations of bone-modifying agents in patients with solid tumor cancers reported in Phase III randomized trials

2012· review· en· W2030471933 on OpenAlexaff
Michael Poon, Liying Zhang, Florence Mok, Kenneth Li, Urban Emmenegger, Erin Wong, Michelle X. Zhou, Henry Lam, Nicholas Lao, Edward Chow

Bibliographic record

VenueJournal of Comparative Effectiveness Research · 2012
Typereview
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineAdverse effectPlaceboNauseaInternal medicineVomitingAdverse Event Reporting SystemOncologyConfoundingBisphosphonateOsteoporosisPathologyAlternative medicine

Abstract

fetched live from OpenAlex

AIMS: The objective of this study is to compare adverse events experienced among different bone-modifying agents. METHODS: A literature search was conducted to identify Phase III bisphosphonate and bone-modifying agent trials reporting adverse effects. Thirty-seven adverse events of interest were identified for six different treatment options. Weighted linear regression modeling was performed on the adverse event proportions with treatment groups, normalized through applying natural log transformations. RESULTS: There were significant differences in adverse events of vomiting (p = 0.045) and osteonecrosis of the jaw (p = 0.017), and combined item events of nausea/vomiting (p = 0.048), hematological and lymphatic system toxicities (p = 0.020), and any respiratory system problem (p = 0.023) between bone-modifying agent and placebo trials. The significant toxicities were observed even after adjusting for the two confounding factors of age and primary cancer site. CONCLUSION: While adverse effects are consistently experienced more frequently in patients receiving bone-modifying agents when compared with placebos, we find that the majority of individual side effects are not significantly more frequent in patients receiving bone-modifying agents compared with placebo.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.026
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0130.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.454
GPT teacher head0.611
Teacher spread0.157 · 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 teacher head, not a consensus.

Study designRandomized trial
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

Citations1
Published2012
Admission routes1
Has abstractyes

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