Renal Neoplasms in Young Adults
Bibliographic record
Abstract
Renal cell carcinoma (RCC) is usually diagnosed in older adults (the median age of diagnosis is 64 years). Although less common in patients younger than 45 years, RCCs in young adults differ in clinical manifestation, pathologic diagnosis, and prognosis. RCCs in young adults are typically smaller, are more organ confined, and manifest at lower stages of disease. The proportion of clear cell RCC is lower in young adults, while the prevalence of familial renal neoplastic syndromes is much higher, and genetic testing is routinely recommended. In such syndromic manifestations, benign-appearing renal cysts can harbor malignancy. Radiologists need to be familiar with the differences of RCCs in young adults and apply an altered approach to diagnosis, treatment, and surveillance. For sporadic renal neoplasms, biopsy and active surveillance are less often used in young adults than in older adults. RCCs in young adults are overall associated with better disease-specific survival after surgical treatment, and minimally invasive nephron-sparing treatment options are preferred. However, surveillance schedules, need for biopsy, decision for an initial period of active surveillance, type of surgery (enucleation or wide-margin partial nephrectomy), and utilization of ablative therapy depend on the presence and type of underlying familial renal neoplastic syndrome. In this pictorial review, syndromic, nonsyndromic, and newer RCC entities that are common in young adults are presented. Their associated unique epidemiology, characteristic imaging and pathologic traits, and key aspects of surveillance and management of renal neoplasms in young adults are discussed. The vital role of the informed radiologist in the multidisciplinary management of RCCs in young adults is highlighted. Online supplemental material is available for this article. ©RSNA, 2022
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".