Acquired aplastic anemia (AA) can present similarly to inherited bone marrow failure syndromes (IBMFS) but treatment differs. AA diagnosis relies on excluding IBMFS; however, genetic testing is not always available, may delay care or be inconclusive. We developed the Predictive Aplastic Score System (PASS), a clinical tool using readily available data to distinguish AA from IBMFS in adults. The training cohort included 212 adults (162 AA, 50 IBMFS). Compared to IBMFS, AA patients were older and more likely to have acute-onset, severe cytopenias. Using logistic regression with LASSO, we selected seven clinical variables for model inclusion: severity, acuity, age, IBMFS red flags, AA-associated conditions, AA-associated somatic changes, and telomere lengths. The model achieved AUC of 0.990 (95% CI: 0.982–0.999), with 100% positive predictive value (PPV) for AA for scores ≥ 30. 86.8% of patients with scores < 0 had IBMFS. We validated PASS in 716 patients from four external cohorts with AUC of 0.977 (95% CI: 0.968–0.987). Threshold analysis confirmed 100% PPV for scores ≥ 30, rapidly diagnosing 80% of AA cases. PASS is a practical and accurate clinical tool that can rapidly distinguish AA from IBMFS for most adult patients. To promote clinical adoption, we developed open-access web calculator (https://pennmedicine.shinyapps.io/passcalc/).

Malignant peritoneal mesothelioma (MPeM) is a rare malignancy with historically poor prognosis. Recent research has started to reveal increasingly prevalent genetic mutations seen in this malignancy. Here, we report a case of complete clinical remission of unresectable, metastatic MPeM with systemic chemotherapy. Immunohistochemistry of our patient’s malignant cytology sample showed loss of Breast Cancer Gene 1-associated protein-1 expression (BAP1). The patient had synchronous diagnoses of primary squamous cell carcinoma of the anus, benign schwannoma and meningioma. Following the completion of 18 cycles of pemetrexed and bevacizumab, the patient has remained in clinical remission for 8 months. We examine the unusual susceptibility of unresectable MPeM to systemic chemotherapy and attribute susceptibility to the molecular milieu created by mutations in multiple DNA repair pathways. We encourage increased testing for and analysis of mutations in DNA repair pathways to improve future treatment outcomes in this rare malignancy.

Extramedullary disease (EMD)—the proliferation of clonal plasma cells in soft tissues without direct bone connection—represents one of the most challenging manifestations of multiple myeloma, associated with aggressive biology, treatment resistance, and poor outcomes. EMD is driven by distinct pathophysiologic mechanisms including downregulation of adhesion molecules, acquisition of high-risk cytogenetic abnormalities (del(17p), gain(1q)), activation of the RAS–MAPK pathway, epigenetic dysregulation such as EZH2 upregulation, and remodeling of the immune microenvironment toward an immunosuppressive, T-cell-depleted phenotype. Conventional therapies, including anti-CD38-based regimens, yield limited efficacy in EMD, with pooled overall response rates of approximately 20% in triple-class-exposed relapsed/refractory disease. T-cell-redirecting therapies have emerged as the most promising treatment strategy. Both chimeric antigen receptor (CAR) T-cell therapy and bispecific antibodies have demonstrated clinically meaningful activity in soft tissue EMD, with CAR T-cell therapy providing the deepest and most durable responses, and dual-targeting bispecific combinations showing particularly encouraging efficacy. Central nervous system (CNS) myeloma, the most devastating form of EMD, has historically carried a dismal prognosis. Emerging retrospective data suggest that both CAR T-cell therapy and bispecific antibodies can achieve meaningful CNS responses with acceptable safety profiles, as part of multimodal approaches incorporating CNS-directed therapies. Despite these advances, EMD remains associated with inferior outcomes even in the immunotherapy era, underscoring the need for strategies targeting the immunosuppressive microenvironment, novel therapeutic approaches, and prospective EMD-focused clinical trials. This review provides a comprehensive overview of the biology, classification, and evolving treatment landscape of both non-CNS and CNS EMD in the era of T-cell-redirecting immunotherapy.

Acquired aplastic anemia (AA) can present similarly to inherited bone marrow failure syndromes (IBMFS) but treatment differs. AA diagnosis relies on excluding IBMFS; however, genetic testing is not always available, may delay care or be inconclusive. We developed the Predictive Aplastic Score System (PASS), a clinical tool using readily available data to distinguish AA from IBMFS in adults. The training cohort included 212 adults (162 AA, 50 IBMFS). Compared to IBMFS, AA patients were older and more likely to have acute-onset, severe cytopenias. Using logistic regression with LASSO, we selected seven clinical variables for model inclusion: severity, acuity, age, IBMFS red flags, AA-associated conditions, AA-associated somatic changes, and telomere lengths. The model achieved AUC of 0.990 (95% CI: 0.982–0.999), with 100% positive predictive value (PPV) for AA for scores ≥30. 86.8% of patients with scores <0 had IBMFS. We validated PASS in 716 patients from four external cohorts with AUC of 0.977 (95% CI: 0.968–0.987). Threshold analysis confirmed 100% PPV for scores ≥30, rapidly diagnosing 80% of AA cases. PASS is a practical and accurate clinical tool that can rapidly distinguish AA from IBMFS for most adult patients. To promote clinical adoption, we developed an open-access web calculator ( https://pennmedicine.shinyapps.io/passcalc/ ).

Background: Overlapping disease features, secondary etiologies, and patient comorbidities contribute to diagnostic ambiguity between pure red cell aplasia (PRCA) and aplastic anemia (AA). Objectives: To evaluate the predictive value of absolute reticulocyte count (ARC) and reticulocyte percentage (RP) thresholds in differentiating PRCA and AA at diagnosis. Design: Retrospective diagnostic accuracy study. Methods: Data on consecutive patients with PRCA or AA at our medical center between 2003-2025 were used to create two Decision Tree binary classification models using ARC and RP. Internal validation utilized leave-one-subject-out cross validation and both models were externally validated with independent cohorts. Results: PRCA (n=19) was classified by ARC ≤ 10.35 x 10 ³ /uL or RP ≤ 0.41% while AA (n=51) was classified by values exceeding these thresholds. Both models achieved an identical AUC 0.92, sensitivity 0.92, and specificity 1.00, with similar AUC after external validation. Conclusions: A greater degree of reticulocytopenia differentiates PRCA from AA.