Clinical Approach to “Pathologically Ambiguous Follicular Lymphoma”: A Real-World Study
Bibliographic record
Abstract
Introduction: The 5th WHO Classification describes a pathologically ambiguous follicular lymphoma (FL) entity as “FL3A with a focal or diffuse growth pattern” but without frank sheets of large cells 1 and recommends selecting treatment based on presenting clinical features. Literature addressing this entity is scarce 2. We therefore sought to assess the incidence and outcomes among patients receiving a pathological diagnosis of ambiguous FL. Methods: A single-center, historical cohort study identified and categorized adult patients with pathologically confirmed FL into one of three categories: low-grade (LG) FL, ambiguous FL, and high-grade (HG) FL (grade 3B +/- DLBCL). We searched our electronic health records (EHR) querying the term “follicular lymphoma” in the “diagnosis” category (Sep. 2013-Jan. 2023) and reviewed paper-based records from Jan. 2008-Aug. 2013. Patients with isolated cutaneous or gastrointestinal disease, previously diagnosed with another non-Hodgkin lymphoma (NHL), or if referred for a clinical trial were excluded. Pathology reports extracted from charts had been reported by one of 3 hematopathologists in our institution. Results: The search yielded 368 EHR charts and 30 paper-based records. We excluded 170 patients for diagnosis prior to 2008 (n=68), referral for clinical trial (n=48), isolated cutaneous or GI FL (n=7), FL in situ (n=4), prior NHL other than FL (n=4), discordant lymphoma (n=2), pediatric FL (n=2), FL was not the diagnosis (n=18), and incomplete pathology report (n=10) or unavailable patient records (n=7). SM reviewed all pathology reports and selected 35 cases that could be interpreted as “ambiguous FL”. SM and SA then reviewed these together; 7 were classified as LG FL, one as HG FL, and 2 discordant lymphomas were excluded, leaving 24 cases of ambiguous FL. As well, 188 patients were classified in the LG and 16 as HG FL. Thus, ambiguous FL comprised 10% of this cohort. Median age at diagnosis in the ambiguous cohort was 63.5 years, and 29% were female. Diagnosis was made by core needle biopsy in six cases and excisional node biopsy in 14 cases; in four cases, the biopsy type was not explicitly stated in the report. At presentation, most had advanced stage disease (n=18, 75%) and met at least one criterion for high tumor burden by GELF criteria (n=13, 54%) 3. Nine of 24 patients (37.5%) were initially managed with a watch and wait approach compared with 111/188 (59%) with LG FL. Of the 24 with ambiguous FL, two (8.3%) remained untreated throughout the duration of follow-up. In addition, 2/24 (8.3%) progressed to DLBCL compared with 28/188 (14.9%) in the LG FL cohort. R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone) was the first-line therapy in 20/24 (83.3%) patients; one received R monotherapy. In comparison, in the LG FL cohort, 37/188 (19.7%) received RCHOP-like therapy (19.7%). One patient progressed within 24 months of chemoimmunotherapy (CIT) compared with 24 in the LG FL cohort. Median progression free survival was similar for patients with LG (9.4 years) and ambiguous (8.3 years) FL, but not reached in the cohort with HG FL (likely due to the small cohort size and number of events) [log-rank p-value=0.84]. The median overall survival was not reached in all three cohorts, with a median follow-up of 7.8, 8.9 and 7.8 years, respectively [log-rank p-value=0.0023]. Discussion: Ambiguous FL is not an infrequent diagnosis in the real-world setting and requires physicians to make a clinical judgment regarding therapy. In our study, patients with ambiguous FL were more likely to be treated within 3 months of diagnosis and to receive anthracycline-based CIT than patients with LG FL. When treated soon after diagnosis with R-CHOP, patients with ambiguous FL have excellent survival outcomes similar to those with LG FL. Expanding this study to other institutions will allow for greater generalizability of these results.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".