Multidisciplinary assessment of patients with extensive stage small cell lung cancer: A geriatric tumor board
Bibliographic record
Abstract
Case presentation and overviewGB, a 74-year-old female with no significant past medical history and active tobacco use disorder of 61 pack-years, underwent a screening computed tomography (CT) of the chest in July 2024.The CT revealed a new, 4.3 � 2.5-cm, spiculated mass in the right upper lobe along with adjacent septal thickening, emphysema, and multiple, stable, subcentimeter pulmonary nodules (Figure 1).A positron-emission tomography-CT confirmed the size and location of the lung lesion, showing intense fluorodeoxyglucose uptake and extensive lymphadenopathy above and below the diaphragm.The scan also revealed numerous additional foci of increased skeletal fluorodeoxyglucose uptake in the axial and left iliac crest regions (Figure 1).A staging brain magnetic resonance image (MRI) showed no suspicious lesions.GB underwent a diagnostic bronchoscopy and endobronchial ultrasound 1 month after her initial presentation.A biopsy of the station 4R lymph node revealed an aggressive neuroendocrine tumor, which tested positive for thyroid transcription factor 1, synaptophysin, and insulinoma-associated protein 11, with an elevated Ki-67 proliferative index.The final diagnosis was extensive-stage small cell lung cancer (ES-SCLC) with bone and liver metastases.Given her advanced age, physicians referred GB to the geriatriconcology multidisciplinary clinic (GO-MDC) to assess her frailty and stratify her chemotherapy toxicity risk. Comprehensive geriatric assessment Functional assessmentWe used the Katz Index of Independence in Activities of Daily Living (ADL) and the Lawton-Brody Instrumental Activities of Daily Living (IADLs) scale to assess independence in ADLs and IADLs, respectively.GB had urge incontinence but was independent in all other ADLs (bathing, dressing, toileting, transferring, and feeding).She managed all IADLs (telephone use, shopping, food preparation, housekeeping, laundry, transportation, responsibility for medication, and handling of finances) by herself.GB is the caregiver to her husband, and she easily performed physical activities between 4 and 10 metabolic equivalents of task.We use the Timed Up and Go test to assess gait stability and fall risk.However, the patient refused to participate in this test during the visit.She was noted to have swift movements during posture change from sitting to standing and could walk without any evidence of gait instability.She had a seemingly normal gait speed when she got up to leave the room at the end of the appointment. Cognitive assessmentWe used the Mini-Cog, a quick screening tool for detecting cognitive impairment.GB scored 1 of 5 points (1 of 3 points on word recall and
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".