Compliance with oral topotecan in patients with non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC)
Bibliographic record
Abstract
7092 Background: Compliance with chemotherapy can affect treatment efficacy and patient safety. Selecting an oral chemotherapy regimen with good tolerability in appropriate patients is important. To determine general level of compliance of oral topotecan, a retrospective analysis was conducted on 3 international open-label, multicenter, 2-arm randomized, phase III studies of patients with NSCLC and SCLC. Methods: Patients were randomized to receive oral topotecan d1–5 q21d as follows: Study 387 (Ramlau et al, Proc ASCO, 2005) 2.3 mg/m 2 /d second-line vs IV docetaxel for NSCLC; Study 389 (Eckardt et al, Proc ASCO, 2005) 1.7 mg/m 2 /d first-line with cisplatin vs etoposide/cisplatin for extensive-disease SCLC; and Study 478 (O’Brien et al, Lung Cancer 2005) 2.3 mg/m 2 /d second-line vs best supportive care for SCLC. Oral topotecan was administered to the patient in the clinic on day 1 of each course and the patient was responsible for self-administering the oral capsules the remaining 4 days of dosing. Patient compliance was defined as 100x(sum of number of caps taken across courses)/(sum of number of caps dispensed across courses), where number of caps taken = number of caps dispensed-number of caps returned. Results: Accrual per arm was (387), 414 patients; (389) 389; (478) 71. In the treated population for all three groups, adherence to oral topotecan was high, with >90% of patients recording at least 90% overall compliance (Table). Mean age (% ≥65 years/%PS 2) was (387) 58.8 years (29.2%/14%), (389) 59.7 (32.6%/13%), and (478) 59.8 (33.8%/27%). Median oral topotecan dose intensity (% target) for each course was (387) 87%, (389) 95%, and (478) 98%. The most common reason for dose reductions or delays was hematological toxicity. Conclusions: Oral topotecan can be administered on an outpatient basis with a high degree of patient compliance in the treated population, which included those ≥65 years and those with poor PS. [Table: see text] [Table: see text]
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.002 |
| 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".