KRAS as a Prognostic and Predictive Marker in Metastatic Non-Small Cell Lung Carcinoma: A Systematic Review
Bibliographic record
Abstract
Metastatic non-small cell lung cancer (NSCLC) poses a significant clinical challenge, prompting a focused investigation into the role of KRAS mutations in prognosis and treatment response. Targeted therapies offer promising avenues for intervention, motivating a comprehensive analysis of existing evidence. Conducted in June 2023, our review delved into MEDLINE (Medical Literature Analysis and Retrieval System Online), Embase, Scopus, and the Cochrane Register of Controlled Trials. Rigorous inclusion and exclusion criteria guided the selection of 12 articles, comprising two randomized controlled trials (RCTs) and 10 observational studies. Multiple investigators independently executed data extraction, evaluating prognostic factors (overall and progression-free survival) and predictive outcomes (treatment and objective response). The Newcastle-Ottawa Scale (NOS) and modified Jadad scores were used for study quality assessment of observational studies and RCTs, respectively. From an initial pool of 120 articles, the 12 selected studies, spanning 2013 to 2022, encompassed 2,845 metastatic NSCLC patients. KRAS mutations, particularly the G12C variant, emerged as a pivotal factor influencing treatment response. Notably, KRAS wild type patients displayed enhanced responses to platinum-based chemotherapy, while those with KRAS mutations exhibited favourable outcomes with immune checkpoint inhibitors (ICIs). The role of KRAS mutations as prognostic indicators in metastatic NSCLC is underscored by this systematic review, with implications for both survival and treatment response. The discernment between KRAS wild type and mutant patients offers insights into tailored therapeutic strategies, with platinum-based chemotherapy and immune checkpoint inhibitors emerging as context-dependent options. Nevertheless, more research is required to solidify the predictive role of KRAS and explore the efficacy of KRAS inhibitors and other targeted therapies, paving the way for refined and personalized interventions in the management of metastatic NSCLC.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".