Prospective Long-Term Follow-Up of Pulmonary Diffusion Capacity Reduction Caused by Dose-Dense Chemotherapy in Patients with Breast Cancer
Bibliographic record
Abstract
Background. Our previous study of pulmonary function in 34 patients with early breast cancer without preexisting lung disease showed that anthracycline- and taxane-based adjuvant dose-dense chemotherapy (DDC) caused a significant 16.4% mean reduction in carbon monoxide diffusing capacity (DLCO). The present study reports the pulmonary and oncological outcomes of these patients on long-term follow-up. Patients and methods. The primary endpoint was DLCO measured by the pulmonary function test (PFT) performed at a median of 27 months after DDC (range, 8–97) in 25 patients without disease recurrence. DLCO values were recorded as a percentage of predicted values according to age, height, and hemoglobin level and analyzed relative to baseline pre-DDC DLCO values. The secondary endpoints were symptoms, additional therapies, and cancer outcomes during a median of 11 years’ follow-up (range, 4.4–11.4). Results. A longitudinal general linear model showed significant effects of time on DLCO and its trend (F(1, 87) = 14.68, p<0.001 and F(1, 87) = 10.26, p=0.002 , respectively). Complementary descriptive analysis showed a significant recovery on the follow-up PFT (75.6% vs. 81.9%, p=0.002 ), but it was still significantly lower than the baseline DLCO (81.9% vs. 92.0%, p=0.003 ). Five patients (20%) still showed a >20% relative DLCO reduction from baseline. Patients with dyspnea or fatigue at later clinical follow-up had a significantly lower DLCO value on the follow-up PFT than nonsymptomatic patients (80.5% vs. 92.1%, p=0.02 ). DLCO recovery was inversely correlated with age (R = −0.39, p=0.05 ), but no significant correlation was found with the length of time until the follow-up PFT or additional therapies. There was no association of DDC-related DLCO reduction with cancer outcomes. Conclusions. The significant reduction in DLCO seen after DDC in patients with potentially curable breast cancer is evident years afterwards, especially in older patients. While most patients partly recover, some will have a lasting symptomatic DLCO impairment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".