Neuropsychological and psychosocial assessment of small and non-small lung cancer patients: a study protocol
Bibliographic record
Abstract
Early diagnosis and effective treatments have favored the survival of cancer patients but have also generated adverse consequences including cognitive impairment and psychological distress, which are related to both disease progression and the side effects of pharmacological agents. However, there is little data in the literature concerning such adverse effects in patients with lung cancer. Here, we describe the protocol of a study aiming to investigate the occurrence of cognitive impairment in patients with non-small-cell lung cancer and small-cell lung cancer undergoing adjuvant therapies or surgery in the year following enrollment. This longitudinal study will recruit around 200 lung cancer patients. To explore the cognitive profile pre- and post-oncological treatment, a cognitive evaluation will be administered to each lung cancer patient at baseline (T0), 4 (T1), and 12 months (T2) after the end of treatments. A cognitive screening will be assessed with the Montreal Cognitive Assessment and Mini-Mental State Examination. Executive functions will be investigated with the Frontal Assessment Battery, the Stroop Color Word test and the phonemic fluency test. Memory and learning will be examined with Rey's auditory verbal learning test, whereas working memory will be assessed with the Digit Span test and the Corsi Block-tapping Test. Finally, attention will be investigated with the Trail Making Test and the Symbol Digit Modalities Test. In addition, perceived cognitive impairment, anxious and depressive symptoms, cognitive reserve, sleep patterns, and patient's quality of life will be also investigated using self-report tools. The cognitive impairment will be identified by adopting the criteria proposed by the International Cognition and Cancer Task Force. This trial received approval from the ethical committee of the Institutes of Scientific Research and Healthcare, IRCCS, European Institute of Oncology (UID_IEO 2027). The results could have relevant implications for managing cognitive impairment and its impact on the quality of life of lung cancer patients. Through a systematic cognitive assessment and its associated risk factors, this study aims to provide valuable insights into clinical practice, enhancing the development of neuropsychological protocols.
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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 | 0.012 | 0.007 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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".