Safety and efficacy of the use of anabolic bone agents in patients with underlying plasma cell dyscrasias: A case series.
Bibliographic record
Abstract
Abstract Introduction: Patients with underlying plasma cell dyscrasias (PCD) such as monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), and multiple myeloma (MM) are at increased risk of developing osteopenia, osteoporosis, fragility fractures, lytic bone lesions, and pathologic fractures as their disease course progresses. Lytic bone lesions often heal infrequently and incompletely, with the highest possibility of healing present only in some patients that achieve long-term stringent remissions (1). Post-menopausal women who develop multiple myeloma with a concurrent diagnosis of osteoporosis have a higher mortality risk (2). Anabolic bone agents are used in post-menopausal women without malignancies who have osteoporosis to decrease their chances for a fragility fracture (3). However, there is concern that use of anabolic therapies for osteoporosis in patients with cancer may fuel occult micro-metastases or stimulate adverse tumor growth. There is no robust scientific evidence that these agents are harmful for patients with PCDs. To date, published data on outcomes of concurrent use of anabolic therapy in the PCD population remains limited. We conducted a retrospective study of all patients within the PSJH network that have been treated with teriparatide, abaloparatide, or romosuzumab with an underlying diagnosis of MGUS, SMM, MM, or AL Amyloidosis. Review Design and Methods: This retrospective study identified patients via electronic medical record (EMR) who both had a documented PCD and anabolic bone therapy within 2 years of their PCD diagnosis. The study inclusion criteria required all patients to be over 50 years of age and have at least 2 years of follow up for their underlying PCD. Patients without adequate follow up information or less than 2 months of treatment were excluded. Data collected included demographics, bone and hematologic diagnoses, treatment duration, prescribing specialty, DEXA scan results, and hematologic disease status at follow-up. Results: •Sample Size: 12 patients (10F, 2M) •Age: Mean 71 years (range 60–88) •Race: All White •Bone Diagnosis: Osteoporosis (n=12) •Plasma Cell Diagnosis: MGUS (n=9), MGRS (n=1), MM (n=2) •Timing: Median interval between bone and hematologic diagnosis was 4 years (range: -10 to +39 years), indicating bone disease often preceded hematologic diagnosis •Anabolic Agents Used: Teriparatide (n=5), Abaloparatide (n=4), Romosozumab (n=3) •Therapy Duration: Mean 18 months (range 12–24 months) •Anabolic Agent Prescribing Specialties: Endocrinology (n=7), Osteology (n=2), Family Medicine (n=2), Rheumatology (n=1) •DEXA T-score Change: Mean improvement of +0.2 (range -0.7 to +1.3) over an average interval of 2.1 years - Baseline T-score: Mean -2.4 - Most recent T-score: Mean -2.2 •Oncology Status at Follow-Up: -Stable MGUS (n=8) -Active MM (n=1) -Deceased (non-PCD-related causes) (n=2) -Lost to follow-up (n=1) Conclusions: In this case series anabolic bone therapy was not associated with a danger signal for higher rates of progression of the underlying plasma cell dyscrasia. These patients generally had stable hematologic disease with an average of 3.5years of follow up for their hematology care with an average of 18 months of overlapping anabolic bone therapy. There was wide variation in which specialty ultimately prescribed the anabolic bone agent. Only 6 patients had an M-protein quantification and 3 had sFLC within 1 month of initiating bone therapy highlighting the need for more collaboration between hematology specialties and bone agent prescribing specialties. These findings suggest anabolic agents may offer a safe and potentially synergistic approach to improving bone health in patients with PCDs. Considering the unique mechanism of action of these agents that can build bone compared to bisphosphonates and RANKL antagonists, we hope that this study will contribute to clinical trial development aimed with the goal of decreasing the morbidity and mortality rates of bone associated pathology in patients with PCDs. References: 1. Terpos E, et al. “Management of bone disease in multiple myeloma: recommendations from the International Myeloma Working Group.” J Clin Oncol. 2018;36(22):2347–2355. 2. Rosko, A. E. (2018). Bone Health and Survival in Woman with Multiple Myeloma. Clinical Lymphoma Myeloma Leukemia, 597-602. 3. Cosman, F et al. “Romosozumab treatment in postmenopausal women with osteoporosis.” NEJM. 2016;375 (16):1532-1543.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".