Clinical Outcomes of Acute Pancreatitis in Patients With Multiple Myeloma

Introduction

Acute pancreatitis (AP) is a common cause of hospitalization and a leading gastrointestinal indication for inpatient care worldwide. In the United States alone, AP accounts for hundreds of thousands of admissions annually and is associated with substantial health care utilization and morbidity.¹ Although gallstones and alcohol use disorder account for most cases, outcomes in AP vary widely based on comorbidity burden and physiologic reserve.²

Multiple myeloma (MM) is a plasma cell malignancy characterized by clonal proliferation of malignant plasma cells and a range of systemic complications that may influence outcomes during acute medical illness.³ Patients with MM frequently experience metabolic disturbances and organ dysfunction related to disease biology and treatment effects, including hypercalcemia, renal impairment, anemia, and immunosuppression. These factors may directly influence the severity, complications, and resource utilization associated with AP. In particular, hypercalcemia, one of the classic complications of MM, has long been recognized as a potential precipitant of pancreatitis, while renal dysfunction and systemic inflammation may exacerbate acute pancreatic injury and contribute to worse outcomes during hospitalization.^4,5

Despite these biologically plausible links, population-level data examining AP outcomes specifically in patients with MM remain limited. Most existing literature consists of case reports or small institutional series, and the broader clinical characteristics and outcomes of AP in the MM population have not been well characterized in large national data sets.⁶ As survival for patients with MM continues to improve with the advent of modern therapies, including proteasome inhibitors, immunomodulatory agents, monoclonal antibodies, and cellular therapies, patients with MM are increasingly likely to present with common acute medical conditions such as AP.⁷ Understanding whether the presence of MM modifies AP severity, complications, or health care utilization therefore has important implications for both inpatient management and health system planning.

Using the National Inpatient Sample (NIS), the largest publicly available all-payer inpatient database in the US, we evaluated hospitalizations for AP among patients with and without MM.⁸ We compared baseline clinical characteristics, metabolic and organ-related complications, and key hospital outcomes, including in-hospital mortality and length of stay, between these groups, and evaluated whether MM was independently associated with adverse outcomes after adjustment for demographic factors and major comorbidities.

Methods

We conducted a retrospective cohort study using the NIS, part of the Healthcare Cost and Utilization Project, sponsored by the Agency for Healthcare Research and Quality. The NIS represents an approximately 20% stratified sample of US hospital discharges. When weighted using discharge weights, the data set enables the generation of nationally representative estimates of inpatient hospitalizations.⁹

Hospitalizations between 2016 and 2022 with a principal diagnosis of AP were identified using International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes (K85.x). The exposure group consisted of patients with a secondary diagnosis of MM identified using ICD-10-CM codes (C90.00, C90.01, C90.02). To minimize misclassification, hospitalizations with diagnoses consistent with monoclonal gammopathy of undetermined significance or smoldering myeloma (D47.2), plasma cell leukemia (C90.1x), chronic pancreatitis (K86.0, K86.1), or pancreatic malignancy (C25.x) were excluded.

Demographic variables included age, sex, race, primary payer, and median household income quartile by zip code. Comorbidity burden was assessed using Elixhauser comorbidity indicators derived from ICD-10-CM codes.¹⁰ Selected comorbidities of clinical relevance included congestive heart failure, renal failure, and coagulopathy. Alcohol use disorder was also assessed, given its established relationship with pancreatitis.

Clinical complications relevant to both pancreatitis and MM biology were identified using diagnosis and procedure codes. These included hypercalcemia, acute kidney injury (AKI), respiratory failure, mechanical ventilation, and vasopressor use. Because physiologic and laboratory parameters required for formal severity classification (eg, Atlanta criteria) are not available in the NIS, severe AP was approximated using markers of organ failure, defined as the presence of respiratory failure, mechanical ventilation, or vasopressor use during hospitalization.

The primary outcomes of interest were in-hospital mortality and hospital length of stay (LOS). Secondary analyses evaluated the prevalence of metabolic and organ-related complications. Because LOS demonstrated a right-skewed distribution, log transformation was applied prior to regression modeling.

All analyses accounted for the complex survey design of the NIS using discharge weights to generate nationally representative estimates.¹¹ Continuous variables were summarized using medians or means as appropriate, and categorical variables were summarized as weighted proportions. Group comparisons were performed using Wilcoxon rank-sum tests for continuous variables and χ² tests for categorical variables.

Multivariable regression models were constructed to evaluate the independent association between MM and clinical outcomes. Survey-weighted logistic regression was used to estimate adjusted ORs (AORs) for in-hospital mortality and severe pancreatitis. A survey-weighted linear regression model using log-transformed LOS was used to estimate the relative percent change in hospitalization duration associated with MM. All models were adjusted for clinically relevant covariates, including age, sex, congestive heart failure, renal failure, and coagulopathy. Covariates were selected a priori based on clinical relevance and to avoid overadjustment for intermediates.

Statistical analyses were performed using R version 4.5.2 with the survey, arrow, dplyr, and broom packages.^12,13 Statistical significance was defined as a 2-sided P value less than .05.

Results

A total of 302,224 hospitalizations for AP were identified during the study period, including 312admissions with MM and 301,912 admissions without MM, corresponding to approximately 1560 weighted MM hospitalizations and 1,509,559 non-MM hospitalizations nationally. MM-associated admissions represented a small proportion of the cohort (< 1%), consistent with the relative rarity of this overlap.

Patients with MM were substantially older than those without MM (median age, 68 vs 51 years), and there was a slightly higher proportion of women (50.6% vs 47.6%). Medicare was the predominant payer among MM hospitalizations (66.9% vs 29.3%), consistent with the older age distribution.

The MM cohort demonstrated a markedly greater comorbidity burden. Congestive heart failure was present in 23.7% of MM hospitalizations compared with 6.8% in patients without MM, while renal failure occurred in 41.3% vs 9.0%, respectively. Complicated hypertension (42.3% vs 11.2%) and coagulopathy (14.1% vs 7.3%) were also more common in MM. In contrast, alcohol use disorder was substantially less prevalent among patients with MM (6.7% vs 29.8%), suggesting a different etiologic profile for pancreatitis in this population.

Clinically relevant metabolic and organ complications were more frequent in the MM group. Hypercalcemia occurred in 7.1% of MM hospitalizations compared with 1.0% in patients without MM (absolute difference, 6.1%). AKI was also significantly more common in the MM cohort (29.5% vs 12.4%). Respiratory failure occurred slightly more frequently among patients with MM (5.8% vs 4.3%), while rates of mechanical ventilation (1.6% vs 1.4%) and vasopressor use (0.3% vs 0.2%) remained low in both groups.

When a composite severe pancreatitis indicator was evaluated—defined by the presence of respiratory failure, mechanical ventilation, or vasopressor use—the prevalence was modestly higher among patients with MM (6.1% vs 4.6%).¹⁴ However, in multivariable analysis adjusting for age, sex, congestive heart failure, renal failure, and coagulopathy, MM was not independently associated with severe pancreatitis (AOR, 0.68; 95% CI, 0.42-1.11; P = .12).

In-hospital mortality was low and similar between groups (MM, 0.64% vs non-MM, 0.66%). In multivariable logistic regression adjusting for major comorbidities, MM was not independently associated with increased mortality (AOR, 0.38; 95% CI, 0.09-1.53; P = .17), with wide CIs reflecting limited event counts.

Despite similar mortality, hospital resource utilization differed between groups. MM hospitalizations had a longer median LOS (4 vs 3 days) and higher median total hospital charges ($37,462 vs $27,927). In survey-weighted linear regression using log-transformed LOS, MM remained independently associated with longer hospitalization, corresponding to an approximately 10.7% increase in LOS compared with non-MM admissions (95% CI, 3.9%-17.9%; P = .0017).

Overall, AP hospitalizations in patients with MM involved an older, more comorbid population with higher rates of hypercalcemia and renal dysfunction, modestly increased severity, and longer hospital stays, without an associated increase in short-term in-hospital mortality.

Discussion

This study represents a large-scale national analysis characterizing the clinical trajectory and inpatient outcomes of AP among patients with MM. Our results indicate that while the MM cohort was older and presented with a substantially higher comorbidity burden, most notably renal failure and congestive heart failure, there was no significant difference in in-hospital mortality compared with the non-MM population. However, MM remained independently associated with an approximately 10.7% increase in LOS and greater health care resource utilization. These findings suggest that AP in MM represents a distinct clinical phenotype characterized by metabolic derangements rather than increased short-term mortality risk.

The etiologic profile of AP in the MM population was distinct, with hypercalcemia occurring 7 times more frequently (7.1% vs 1.0%) despite a nearly 5-fold lower prevalence of alcohol use disorder. Hypercalcemia is a recognized precipitant of pancreatitis, with proposed mechanisms involving calcium-induced intrapancreatic trypsinogen activation and ductal obstruction from calcium plugs.^5,15,16 In MM, this metabolic disturbance is primarily driven by cytokine-mediated osteoclast activation.¹⁷These findings suggest that clinical management of AP in the setting of MM should prioritize the identification and treatment of hypercalcemia, as it may be an important contributor to pancreatic injury in this population.

Despite the markedly higher prevalence of baseline renal failure (41.3%) and AKI (29.5%) in the MM cohort, adjusted mortality rates did not differ significantly from those of patients without MM. This observation is noteworthy, as AKI is typically a potent predictor of adverse outcomes in AP.¹⁸ One possible explanation is that some renal impairment in this cohort reflected underlying myeloma-
related kidney disease rather than AP-related multiorgan failure, although this cannot be confirmed in administrative data.¹⁹ Additionally, the absence of a difference in in-hospital mortality may reflect the benefits of contemporary multidisciplinary care and aggressive supportive interventions in patients with hematologic malignancies.^20,21

The observed increases in LOS and hospital charges likely reflect the diagnostic and therapeutic complexity of this comorbid population. Managing AP in the context of MM requires balancing aggressive fluid resuscitation, essential for both pancreatitis and hypercalcemia, against the risk of volume overload in a cohort with high rates of heart failure (23.7%). The need for careful fluid and electrolyte management and close clinical monitoring likely contributes to the independent association between MM and longer hospitalizations.²²

Several limitations of this study warrant consideration. As an analysis of administrative claims data, our study is subject to potential coding inaccuracies or omissions. Furthermore, the NIS lacks granular laboratory and imaging data, precluding a more detailed assessment of AP severity based on the Ranson or Bedside Index of Severity in Acute Pancreatitis scores. We also lacked information regarding the specific stage of myeloma or the exact chemotherapy regimens being administered at the time of admission, which could theoretically influence pancreatic health. Finally, the retrospective nature of the database does not allow for long-term follow-up beyond the index hospitalization. Residual confounding due to unmeasured factors, including disease severity and treatment status, remains possible. Despite these limitations, the use of a nationally representative data set provides the largest available cohort to date to examine this rare but clinically significant intersection.

Conclusion

AP hospitalizations in patients with MM occur in an older and more medically complex population with markedly higher rates of hypercalcemia and AKI. Despite this increased metabolic and comorbidity burden, MM was not independently associated with higher in-hospital mortality, although it was associated with longer hospital stays and greater resource utilization. These findings suggest that although pancreatitis in patients with MM presents distinct clinical challenges, short-term in-hospital mortality does not appear to be higher despite greater metabolic and comorbidity burden. Recognition of myeloma-related metabolic complications, particularly hypercalcemia and renal dysfunction, remains important in the clinical management of pancreatitis in this population.

Corresponding Author

Mohammad Ahsen Soomro, MD, MPH

501 S. Washington Ave, Suite 1000

Scranton, PA 18503

Conflict of Interest Statement

The authors have no financial or proprietary interests in any material discussed in this article.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or nonprofit sectors.

References

1. Peery AF, Crockett SD, Barritt AS, et al. Burden of gastrointestinal, liver, and pancreatic diseases in the United States. Gastroenterology. 2015;149(7):1731-1741.e3. doi:10.1053/j.gastro.2015.08.045
2. Kylänpää L, Rakonczay Z Jr, O’Reilly DA. The clinical course of acute pancreatitis and the inflammatory mediators that drive it. Int J Inflam. 2012;2012:360685. doi:10.1155/2012/360685
3. Rajkumar SV. Multiple myeloma: 2024 update on diagnosis, risk-stratification, and management. Am J Hematol. 2024;99(9):1802-1824. doi:10.1002/ajh.27422
4. Fayaz A, Shah AH, Khan MA, Parveen S. Multiple myeloma presenting as hypercalcemia-induced acute severe pancreatitis: a case report. Gastro Hep Adv. 2024;4(8):100549. doi:10.1016/j.gastha.2024.09.004
5. Gieszinger G, Kui B, Hegyi P, et al. Hypercalcemia causes more severe acute pancreatitis: an international multicenter cohort study. J Clin Med. 2025;14(17):6304. doi:10.3390/jcm14176304
6. Mishra SB, Azim A, Mukherjee A. Multiple myeloma presenting as acute pancreatitis. Am J Emerg Med. 2017;35(9):1385.e1-1385.e2. doi:10.1016/j.ajem.2017.06.009
7. Kumar SK, Callander NS, Adekola K, et al. NCCN Guidelines Insights: multiple myeloma, version 1.2025. J Natl Compr Canc Netw. 2025;23(5):132-140. doi:10.6004/jnccn.2025.0023
8. Overview of the National (Nationwide) Inpatient Sample (NIS). Agency for Healthcare Research and Quality. Updated May 6, 2026. Accessed February 21, 2026. https://hcup-us.ahrq.gov/nisoverview.jsp
9. Houchens R, Ross D, Elixhauser A, Jiang J. Nationwide Inpatient Sample (NIS) redesign final report. US Agency for Healthcare Research and Quality. HCUP Methods Series Report 2014-04. April 2014. http://www.hcup-us.ahrq.gov/reports/methods/methods.jsp
10. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8-27. doi:10.1097/00005650-199801000-00004
11. Khera R, Angraal S, Couch T, et al. Adherence to methodological standards in research using the National Inpatient Sample. JAMA. 2017;318(20):2011-2018. doi:10.1001/jama.2017.17653
12. R Core Team. The R Project for Statistical Computing. 2024. https://www.R-project.org/
13. Lumley T. Analysis of complex survey samples. J Stat Softw. 2004;9(8):1-19. doi:10.18637/jss.v009.i08
14. Sarr MG. 2012 revision of the Atlanta classification of acute pancreatitis. Pol Arch Med Wewn. 2013;123(3):118-124. doi:10.20452/pamw.1627
15. Jo IH, Paik CN. Acute pancreatitis with hypercalcemia as initial manifestation of multiple myeloma. Korean J Gastroenterol. 2020;75(4):220-224. doi:10.4166/kjg.2020.75.4.220
16. Meltzer LE, Palmon FP, Paik YK, Custer RP. Acute pancreatitis secondary to hypercalcemia of multiple myeloma. Ann Intern Med. 1962;57:1008-1012. doi:10.7326/0003-4819-57-6-1008
17. Roodman GD. Pathogenesis of myeloma bone disease. Leukemia. 2009;23(3):435-441. doi:10.1038/leu.2008.336
18. Shi N, Sun GD, Ji YY, et al. Effects of acute kidney injury on acute pancreatitis patients' survival rate in intensive care unit: a retrospective study. World J Gastroenterol. 2021;27(38):6453-6464. doi:10.3748/wjg.v27.i38.6453
19. Hutchison CA, Batuman V, Behrens J, et al; International Kidney and Monoclonal Gammopathy Research Group. The pathogenesis and diagnosis of acute kidney injury in multiple myeloma. Nat Rev Nephrol. 2011;8(1):43-51. doi:10.1038/nrneph.2011.168
20. Azoulay E, Pickkers P, Soares M, et al; Efraim investigators and the Nine-I study group. Acute hypoxemic respiratory failure in immunocompromised patients: the Efraim multinational prospective cohort study. Intensive Care Med. 2017;43(12):1808-1819. doi:10.1007/s00134-017-4947-1
21. Kumar SK, Rajkumar SV, Dispenzieri A, et al. Improved survival in multiple myeloma and the impact of novel therapies. Blood. 2008;111(5):2516-2520. doi:10.1182/blood-2007-10-116129
22. Costa LJ, Brill IK, Omel J, Godby K, Kumar SK, Brown EE. Recent trends in multiple myeloma incidence and survival by age, race, and ethnicity in the United States. Blood Adv. 2017;1(4):282-287. doi:10.1182/bloodadvances.2016002493