Quantitative sensory profiles of upper extremity chemotherapy induced peripheral neuropathy: Are there differences in sensory profiles for neuropathic versus nociceptive pain?
Bibliographic record
Abstract
Aims The aim of this study was to define the sensory phenotypes of taxane-induced peripheral neuropathy (TIPN) between neuropathic and nonneuropathic symptoms in a breast cancer population to identify future targets for mechanism-based pain management.Methods Participants (n = 48) with stage I–III breast cancer. Self-report questionnaires and quantitative sensory testing were used to assess sensory symptoms. The self-report version of the Leeds Assessment for Neuropathic Symptoms and Signs (S-LANSS) divided the groups into neuropathic and nonneuropathic sensory phenotypes. In total, five visits over approximately 8 months assessed each participant from pre-chemotherapy to 6 months post-chemotherapy.Results Out of 191 nerve assessments, 150 had an S-LANSS <12 defined as “nonneuropathic” and 41 scored >12, which was defined as “neuropathic.” Numeric Pain Rating Scale (NPRS) was analyzed based on percentages of those experiencing 1+ pain (graded 1/10 or higher) versus no pain. The neuropathic group had 82.9% of 1+ pain vs. 28.7% in the nonneuropathic group (odds ratio = 7.49; 95% confidence interval, 2.76–20.3; P = 0.001). The neuropathic group reported impaired function on the Disability of the Arm, Shoulder, and Hand (DASH) questionnaire (P = 0.002). Heat pain threshold resulted in statistical differences for the left hand but not the right hand in the neuropathic group (P = 0.05). No other quantitative data on warm/cool or cold or vibration demonstrated sensory differences between the groups.Conclusions Few differences in sensory profiles measured using quantitative sensory testing (QST) were found. Heat pain thresholds were normalized, possibly suggesting that the neuropathic group retained C-fiber and transient potential vanilloid 1 (TRPV1) function. Participants with neuropathic pain demonstrated significant differences with increased pain and decreased function.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".