Effects of Acetaminophen Exposure on Outcomes of Patients Receiving Immune Checkpoint Inhibitors for Advanced Non-Small-Cell Lung Cancer: A Propensity Score-Matched Analysis
Bibliographic record
Abstract
(1) Background: Several studies have investigated potential interactions between immune checkpoint inhibitors (ICIs) and commonly prescribed medications. Although acetaminophen (APAP) has not been considered susceptible to interaction with ICIs, recent research has shown that detectable plasma levels of this drug can hinder the efficacy of PD-1/PD-L1 blockade therapies. A reliable assessment of the potential interaction between APAP and ICIs in advanced non-small cell lung cancer (NSCLC) patients would be worthwhile since it is often prescribed in this condition. We sought to evaluate the impact of the concomitant use of APAP in patients with advanced NSCLC on PD-1/PD-L1 blockade using real-world evidence. (2) Methods: This study included consecutive patients with histologically proven stage IV NSCLC who underwent first-line therapy with pembrolizumab as a single agent or in combination with platinum-based chemotherapy, or second-line therapy with pembrolizumab, nivolumab, or atezolizumab. The intensity of APAP exposure was classified as low (therapeutic intake lasting less than 24 h or a cumulative intake lower than 60 doses of 1000 mg) or high (therapeutic intake lasting more than 24 h or a total intake exceeding 60 doses of 1000 mg). The favorable outcome of anti-PD-1/PD-L1 therapies was defined by durable clinical benefit (DCB). Progression-free survival (PFS) and overall survival (OS) were relevant to our efficacy analysis. Propensity score matching (PSM) methods were applied to adjust for differences between the APAP exposure subgroups. (3) Results: Over the course of April 2018 to October 2022, 80 patients were treated with first-line pembrolizumab either as single-agent therapy or in combination with platinum-based chemotherapy. During the period from June 2015 to November 2022, 145 patients were given anti-PD-1/PD-L1 blockade therapy as second-line treatment. Subsequent efficacy analyses relied on adjusted PSM populations in both treatment settings. Multivariate testing revealed that only the level of APAP and corticosteroid intake had an independent effect on DCB in both treatment lines. Multivariate Cox regression analysis confirmed high exposure to APAP and immunosuppressive corticosteroid therapy as independent predictors of shorter PFS and OS in both treatment settings. (4) Conclusions: Our findings would strengthen the available evidence that concomitant intake of APAP blunts the efficacy of ICIs in patients with advanced NSCLC. The detrimental effects appear to depend on the cumulative dose and duration of exposure to APAP. The inherent shortcomings of the current research warrant confirmation in larger independent series.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".