Continuous reference intervals for pediatric testosterone, sex hormone binding globulin and free testosterone using quantile regression
Bibliographic record
Abstract
Testosterone (T), sex hormone binding globulin (SHBG), free testosterone (FT) and bioavailable testosterone (BAT) are commonly employed tests in pediatric endocrinology and all require age-dependent reference intervals for interpretation. The common methods used to derive these reference intervals require decisions about data shape and/or age partition thresholds, which can result in sharp differences between age groups, particularly for pubescent children. Partitioning also results in a form of data loss, where data from one age-bin is completed disconnected from the adjacent age-bins. Non-parametric continuous reference intervals methods have previously been developed to avoid some of these drawbacks. These strategies use all the available data and smooth transitions between ages avoiding partitioning. However, the fitting process involves selection and adjustment of many parameters and it can be difficult to maintain a reproducible approach. Here we provide a workflow for non-parametric continuous reference intervals applied to T, FT, BAT, and SHBG using the R language quantregGrowth package. T measurements were determined by LC-MS/MS, FT and BAT were calculated, and SHBG was measured on the Roche Cobas e601. The continuous interval methodology is described in detail with code examples and illustrations for reproducibility.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".