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Record W2530917533 · doi:10.1097/brs.0000000000001825

Focus Issue II in Spine Oncology

2016· article· en· W2530917533 on OpenAlexaff
Niccole Germscheid, Charles G. Fisher

Bibliographic record

VenueSpine · 2016
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsVancouver Coastal HealthVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineInternal medicineOncologyFamily medicine

Abstract

fetched live from OpenAlex

Table 1 summarizes the recommendations from the AOSpine Knowledge Forum Tumor spine oncology focus issue. The recommendations span a breadth of clinical dilemmas and are the end result of 2 years of concerted effort among dedicated health care professionals. Structured meetings and surveys with experienced oncology clinicians and methodologists integrated with thorough systematic reviews culminated in the 14 articles and their subsequent recommendations. The Grading of Recommendations Assessment, Development, and Evaluation (GRADE) methodology1 was used for this process. Although GRADE provides a reliable process for arriving at trustworthy clinical recommendations, the consumer must understand the meaning and effects of the two recommendations (strong and weak) to apply them.TABLE 1: Summary of Spine Oncology Treatment Recommendations From the AOSpine Knowledge Forum TumorTABLE 1 (Continued): Summary of Spine Oncology Treatment Recommendations From the AOSpine Knowledge Forum TumorTABLE 1 (Continued): Summary of Spine Oncology Treatment Recommendations From the AOSpine Knowledge Forum TumorTABLE 1 (Continued): Summary of Spine Oncology Treatment Recommendations From the AOSpine Knowledge Forum TumorTABLE 1 (Continued): Summary of Spine Oncology Treatment Recommendations From the AOSpine Knowledge Forum TumorTABLE 1 (Continued): Summary of Spine Oncology Treatment Recommendations From the AOSpine Knowledge Forum TumorTABLE 1 (Continued): Summary of Spine Oncology Treatment Recommendations From the AOSpine Knowledge Forum TumorA consensus strong recommendation allows clinicians to confidently apply an intervention “to all or almost all the patients in all or almost all the circumstances without thorough (or even cursory) review of the underlying evidence and without a detailed discussion with the patient.”2 An example would be the recommendation of neoadjuvant chemotherapy and en bloc resection for osteosarcoma of the spine. The reader must be aware that strong recommendations are sometimes made in the setting of low or very low quality evidence. This is not intuitive, given that traditional recommendations only considered evidence and not expert opinion or patient values. This is the practical value of GRADE, as it offers direction in a setting of limited evidence. Evidence, of course, is still important. For example, a clinician would place a higher value on a strong recommendation in a setting of high or moderate quality evidence than low or very low quality evidence. The connotation of the word weak, historically may lead clinicians to dismiss a weak recommendation as poor and not worth pursuing. This is a classic misnomer and not the case for the GRADE weak recommendation. A consensus weak recommendation is an endorsement of the intervention, but the magnitude is less and circumstances altered compared with a strong recommendation. Weak recommendations can be applied to most patients, however, not all patients. To initiate a weak recommendation, a clinician considers fundamental variables impacting the strength of the recommendation: the quality of evidence, risk and benefit of the intervention, clinician's experience, patient preferences, and cost-effectiveness. Thus, a weak recommendation becomes a shared decision-making process with the patient often culminating in the values and preference of the patient. These concepts are very germane to decision-making in oncology. An example would be the treatment of Ewing sarcoma of the spine. Radiation and chemotherapy are absolute treatments, but en bloc resection, which probably improves survival and decreases local recurrence, is a high-risk procedure, which could induce significant impairment and harm. Most clinicians would recommend en bloc resection and patients consent to it, but not everyone would. With a clear understanding of the derivation and meaning of a strong and weak recommendation, the application and impact of these recommendations on clinical practice can be appreciated. We are hopeful these recommendations will serve as trustworthy guidelines and aid the reader in real-life decisions around spine oncology management.

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)0.036
metaresearch head score (Gemma)0.130
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: Editorial · Consensus signal: none
Teacher disagreement score0.078
Threshold uncertainty score0.261

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.130
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0100.005
Science and technology studies0.0030.002
Scholarly communication0.0070.008
Open science0.0050.007
Research integrity0.0170.010
Insufficient payload (model declined to judge)0.0780.032

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 head0.019
GPT teacher head0.325
Teacher spread0.306 · 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
GenreEditorial

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".

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Citations7
Published2016
Admission routes1
Has abstractyes

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