Introduction

Leukemia is a hematologic malignancy that poses a significant challenge due to its rapid proliferation of immature blood cells, affecting individuals of all ages. As of January 1, 2019, there were an estimated 166,412 people with leukemia in the United States, based on diagnoses made between 2014 and 2018. This statistic underscores the significance of leukemia as a public health concern [1]. Thus, it is important to examine deeper into the factors that shape prognosis and mortality among those diagnosed with this condition.

Research has indicated that malnutrition is prevalent in 30- 85% of individuals diagnosed with cancer, thus corroborating it to be a critical factor that influences both disease progression and patient outcomes [2,3]. The roots of malnutrition in acute leukemia are multifaceted, stemming from the disease’s metabolic demands, treatment-related side effects, and inadequate dietary intake. This nutritional deficit can exacerbate disease-related complications, compromising the immune system, impeding the healing process, and diminishing the body’s capacity to tolerate and respond to treatment [4].

Previous studies have established a broad connection between poor nutritional status and undesirable outcomes, such as prolonged hospital stays, increased admission rates, and elevated cancer-related mortality [5,6]. Nutritional status is assessed by considering six potential indicators of malnutrition, with a diagnosis of malnutrition deemed appropriate if two or more criteria are met: insufficient energy intake, weight loss, loss of muscle mass, loss of subcutaneous fat, localized or generalized fluid retention, and diminished functional capacity measured through hand grip strength [7]. However, despite its undeniable significance, the precise impact of malnutrition on acute leukemia’s progression and treatment outcomes remains an area in need of further exploration.

To bridge this knowledge gap, this retrospective study leveraged data from a large cohort of hospitalized acute leukemia patients in the United States. Our analysis included patients hospitalized with acute myeloid leukemia or acute lymphocytic leukemia. The aim was to comprehensively assess the impact of malnutrition on disease progression and clinical outcomes, ultimately shedding light on this critical aspect of leukemia care.

Materials and methods

Data source: Our study relied on the data provided by the NIS database, which was developed as an integral component of the Healthcare Cost and Utilization Project (HCUP), generously sponsored by the Agency for Healthcare Research and Quality (AHRQ). This massive all-payer inpatient healthcare database offers a wealth of public information to researchers and boasts an impressive sample size that approximates 20% of stratified discharges from community hospitals across America [8]. Employing a systematic sampling design, this comprehensive resource is crafted from state-initiated patient databases, generating distinctive discharge records that encompass vital medical information. These records include primary and secondary diagnoses, alongside procedures conducted during hospitalization. Additionally, each record incorporates demographic details, comorbidities, severity of illness, and mortality risk based on All Patient Refined DiagnosisRelated Groups (APR-DRG). Other incorporated elements consist of the Length of Hospital Stay (LOS), teaching status, hospital location, geographic region, and an estimated median household income quartile based on the patient’s zip code. Furthermore, primary payer information, discharge disposition, and in-hospital mortality are meticulously documented in each record.

Study design and population: Since Leukemia is often diagnosed in childhood but can also affect individuals of all ages, our study encompassed patients both below and above 18 years old. The National Inpatient Sample for 2019-2020 was analyzed to specifically identify patients who had been admitted with a diagnosis of Acute Myeloid or Lymphocytic Leukemia. Subsequently, the patient cohort was segregated into two distinct groups based on their respective nutritional statuses: one group comprising individuals without malnutrition and the other including those with concurrent malnutrition.

Outcomes: The primary objective of the study was to evaluate and contrast mortality rates between two groups. In addition to this vital outcome measure, various secondary parameters, such as length of hospitalization and total hospital charges, were examined to gain a more comprehensive understanding of patient outcomes. These metrics provided insights into resource utilization patterns within each population. Furthermore, the study compared the Charlson comorbidity index, a tool capable of addressing numerous confounding factors, between patients with and without concomitant frailty.

Statistical analysis: The statistical analysis in this study prioritized ensuring the reliability and validity of results. We utilized Stata 17 software with weighted samples to align with Healthcare Cost and Utilization Project regulations when using the NIS database for national estimates. Continuous variables were represented by mean values and standard deviations, while categorical variables were expressed as percentages. For group comparisons, the «Student’s t-test» on Stata was applied to continuous variables, and the «Chi-square test» was used for categorical variables. The multivariate analysis carefully considered variables that showed significant differences in outcomes from univariate analysis (p-value less than 0.2) and also included crucial determinants regardless of their statistical significance. It involved calculating odds ratios for all outcomes, adjusting for factors such as age, gender, ethnicity, insurance coverage status, hospital location, teaching status, bed size, and the Charlson comorbidity index to provide a comprehensive understanding of the data.

Results

A total of 24855 patients with the primary discharge diagnosis of acute Leukemia were included in the study. Among these, 3425(13.7%) had concomitant malnutrition, while the remaining 21430 had no malnutrition. The mean age of patients with Leukemia and malnutrition was 43.15 years (+/-25.80) compared to 35.26 years (+/-26.28) for those without malnutrition (p<0.001). Younger patients (<18 years) had fewer instances of malnutrition (22.04% vs. 35.49%, p<0.001), whereas older patients exhibited a higher prevalence of malnutrition (Aged 46-64: 23.8% vs 18.57%, Aged>65: 26.57% vs 18.88%, p<0.001). A more significant proportion of patients diagnosed with malnutrition were found to be covered by Medicare (28.75% vs 21.44%, p<0.001), whereas those without malnutrition exhibited a higher prevalence of Medicaid insurance (31.41% vs 24.11%, p<0.001). The representation of individuals with private insurance was nearly equivalent across both groups (43.12% vs 44.95%, p<0.001). Surprisingly, there was a higher prevalence of people without insurance in the group without malnutrition (4.04% vs 3.09%, p<0.001). Acute Leukemia with Malnutrition had a larger proportion of patients with fluid and electrolyte disorders (50.36% vs 31.68%, <0.001). A higher proportion of heart failure was noted in patients with malnutrition (8.03% vs 5.04%, p=0.001). Leukemia without malnutrition had fewer patients who underwent Hematopoietic stem cell transplant than patients with malnutrition (10.69% vs 20.15%, p<0.001). Conversely, a larger proportion of patients without malnutrition had undergone chemotherapy (2.66% vs 0.73%, p= 0.002). A larger percentage of patients with malnutrition were discharged to homes with home health services (23.43% vs. 13.61%, p<0.001), while patients without malnutrition had a large percentage that was discharged to homes and skilled nursing facilities (75.74% vs. 70.85% & 9.9% vs. 5.35%, p<0.001). Smaller hospitals had a higher proportion of patients without malnutrition (14.28% vs 9.78%, p<0.001), while larger hospitals had a greater percentage of patients with malnutrition (78.54% vs 64%, p<0.001). Additionally, non-teaching hospitals tended to have fewer patients with malnutrition and more patients without malnutrition (2.77% vs 5.76%, p=0.002) (Table 1).

Table 1: Comparison of baseline characteristics of acute leukemia patients with and without malnutrition.

Table 2: Univariate and multivariate regression analysis of odds of mortality in acute leukemia patients with and without malnutrition.

Univariate regression analysis revealed an association between increased mortality and concurrent malnutrition in patients with acute Leukemia (OR 3.33, 95% CI: 2.49-4.45, p<0.001). Upon conducting multivariate logistic regression analysis to adjust for confounding variables, it was determined that malnutrition independently contributes to higher mortality among hospitalized acute leukemia patients (OR 2.89, 95% CI: 2.11-3.94, p<0.001) (Table 2).

Likewise, Tables 3 and 4 present the results of univariate and multivariate analyses for length of stay and total hospitalization charges. Following adjustment for confounding factors, the multivariate regression analysis indicated a significant increase in both length of stay (+9.1 Days 95% CI: 7.01-11.19, p<0.001) and total hospitalization charges (+177994 USD, 95% CI: 122573-2334512, p<0.001) among acute leukemia patients with concurrent malnutrition.

Table 3: Univariate and multivariate regression analysis of length of hospitalization in acute leukemia patients with and without malnutrition.

Table 4: Univariate and multivariate regression analysis of the total cost of hospitalization in acute leukemia patients with and without malnutrition.

Discussion

Our comprehensive study revealed the alarming impact of malnutrition on hospitalized acute leukemia patients, with a staggering threefold increase in mortality. Additionally, our findings also highlighted its substantial influence on prolonged hospital stays and increased overall hospitalization costs. Research by Deenadayalan et al. shed light on the prevalence of malnutrition in Diffuse Large B Cell Lymphoma (DLBCL), revealing that 7% of chemotherapy-admitted patients suffered from concurrent malnutrition [9]. Another study conducted by Park et al. reported a higher range of 10-20% for the prevalence of malnutrition in DLBCL patients [10]. In alignment with these insights, our own research indicated a notable 13% prevalence rate of malnutrition among acute leukemia patients.

In our study, it was found that a higher percentage of Hematopoietic Stem Cell Transplants (HSCT) occurred in malnourished patients compared to those without malnutrition. According to Kim et al. HSCT failures are recognized as potential and devastating complications of malnutrition, and malnutrition is also considered a poor prognostic factor for outcomes in HSCT patients [11]. The increased occurrence of HSCT in our study’s cohort of malnourished patients is likely due to the fact that HSCT failures necessitate multiple repeat interventions and procedures within this patient group. Previous studies have extensively elucidated the association between malnutrition and adverse outcomes in leukemia patients undergoing HSCT.

Amiri Khosroshahi et al. conducted a comprehensive singlecenter observational, longitudinal, and prospective study involving 98 adult leukemia patients who had undergone hematopoietic stem cell transplantation [12]. The study focused on evaluating outcomes such as mortality rates, the occurrence of oral mucositis, infection incidences, and readmission rates. Their findings suggested that malnutrition correlated with an increased risk of infections and readmissions; however, it did not show any significant difference in overall survival [12]. In contrast to their conclusions, our own research indicated a higher incidence of mortality among malnourished patients. It is important to note that while the aforementioned study had a relatively small cohort size, our study encompassed a larger group, including both transplant candidates and non-transplant candidates, for better representation.

Our study revealed a striking disparity in the rates of chemotherapy undergone by patients with malnutrition compared to those without. This discrepancy can be attributed to the formidable toxicity of induction and maintenance therapies, rendering them particularly challenging for individuals grappling with malnutrition. Not only does malnutrition compromise immune function, but it also undermines overall physical endurance and muscle capability, profoundly affecting quality of life. Additionally, it significantly attenuates the body’s capacity to withstand chemotherapy, heightening susceptibility to treatment-related toxicity and complications while concurrently diminishing survival prospects.

Van Cutsem et al. conducted an extensive study highlighting the profound impact of chemotherapy on the immune system. They noted that when combined with malnutrition, these effects can drastically reduce a patient’s ability to tolerate the adverse effects of chemotherapy, ultimately leading to decreased compliance rates and overall survival outcomes [13].

Similarly, Malihi et al. conducted a prospective study to comprehensively assess the alterations in the nutritional status of leukemia patients both prior to and following induction therapy [14]. Their cohort comprised 63 leukemia patients who were subjected to induction chemotherapy. The findings revealed that 19.4% of these patients experienced malnutrition before undergoing induction chemotherapy, while after the completion of therapy, this figure escalated significantly to 76.1% [14]. This data underscores the rationale behind our observation that individuals with preexisting malnutrition were less inclined to undergo chemotherapy based on our results.

Several recent studies have delved into the profound impact of malnutrition on healthcare resource utilization and patient outcomes in various severe health conditions. A prospective study by Lim et al. meticulously utilized Subjective Global Assessment to identify malnourished patients, enrolling a substantial cohort of 818 individuals. The extensive analysis revealed compelling evidence linking malnutrition to prolonged hospital stays, escalated treatment expenses, and heightened readmission rates [15]. Furthermore, Inciong et al. conducted an expansive multicountry investigation across Asia due to the pervasive prevalence of malnutrition within the continent. Their findings underscored a significant upsurge in total hospitalization costs attributable to malnutrition-related factors, amounting to an estimated annual expenditure exceeding 30 billion dollars for additional treatments [16].

Malnourishment not only increases the likelihood of sickness and death among hospital patients, but it also contributes to a substantial increase in healthcare expenses. The prolonged duration of hospitalization and increased expenses could signify the intricate nature and seriousness of clinical intervention needed for malnourished patients. This underscores the need for a more thorough and holistic approach to their treatment, potentially involving extra resources such as specialized medical knowledge, personalized care plans, and continuous support services. By implementing a comprehensive screening tool, healthcare providers can effectively identify at-risk patients and provide them with the necessary care, ultimately leading to enhanced clinical outcomes and reduced healthcare costs.

Several constraints need to be recognized when interpreting the results of this study. Firstly, it’s important to acknowledge that the analysis was based on retrospective data from the NIS 2019- 2020 database, which relies on the accuracy and completeness of recorded data. Variations in coding practices across healthcare facilities could significantly impact these findings. It would be beneficial for future studies to explore utilizing prospective study designs to capture detailed clinical information directly, thereby minimizing variations and potential inaccuracies associated with databases’ retrospective nature. Additionally, implementing a more comprehensive sampling approach that includes both hospitalized and outpatient cases should also be considered, as it may provide a more holistic view of the subject matter.

The absence of malnutrition severity in the NIS data could significantly impact the findings and their real-world relevance. By solely focusing on hospitalized patients, there is a potential for bias, as it excludes less severe cases treated on an outpatient basis. Moreover, the study overlooks consideration of various treatment methods that might have a substantial influence on the analysis of outcomes. Despite its limitations, this study provides valuable initial insights into the relationship between malnutrition and hospitalized acute leukemia patients. It suggests a need for additional prospective research to validate and build upon its findings with more depth and context into different aspects affecting these patients’ nutritional status

Conclusion

This retrospective study analyzed a compelling association between malnutrition and adverse outcomes in patients hospitalized with acute leukemia. The findings underscore the critical importance of addressing and mitigating malnutrition as an integral component of comprehensive care for this vulnerable patient population. Beyond serving as a prognostic marker, understanding the impact of malnutrition on clinical outcomes can inform tailored interventions and strategies aimed at improving the overall prognosis and quality of life for individuals with acute leukemia. Further research should delve into the underlying mechanisms linking malnutrition and poor outcomes, paving the way for targeted therapeutic interventions and enhanced supportive care strategies in the management of acute leukemia patients.

References

1. Centers for Disease Control and Prevention. Hematologic Cancer Incidence, Survival, and Prevalence. USCS Data Brief. Atlanta, GA: Centers for Disease Control and Prevention, US Department of Health and Human Services. 2022; 30.
2. Hébuterne X, Lemarié E, Michallet M, de Montreuil CB, Schneider SM, & Goldwasser F. Prevalence of malnutrition and current use of nutrition support in patients with cancer. JPEN. Journal of parenteral and enteral nutrition. 2014; 38(2): 196-204. https://doi.org/10.1177/0148607113502674.
3. Bozzetti F, Mariani L, Lo Vullo S. The nutritional risk in oncology: a study of 1,453 cancer outpatients. Supportive care in cancer: official journal of the Multinational Association of Supportive Care in Cancer. 2012; 20(8): 1919-1928. https://doi.org/10.1007/s00520-012-1387-x.
4. World Health Organization (WHO). Nutrition. www.who.int/health-topics/nutrition#tab=tab_1.
5. Marshall KM, Loeliger J, Nolte L, Kelaart A, & Kiss NK. Prevalence of malnutrition and impact on clinical outcomes in cancer services: A comparison of two time points. Clinical nutrition (Edinburgh, Scotland). 2019; 38(2): 644-651. https://doi.org/10.1016/j.clnu.2018.04.007.
6. Correia MI, & Waitzberg DL. The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis. Clinical nutrition (Edinburgh, Scotland). 2003; 22(3): 235-239. https://doi.org/10.1016/s0261-5614(02)00215-7.
7. White JV, Guenter P, Jensen G. Consensus statement: Academy of Nutrition and Dietetics and American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). JPEN. Journal of parenteral and enteral nutrition. 2012; 36(3): 275-283. https://doi.org/10.1177/0148607112440285.
8. Khera R, Angraal S, Couch T. Adherence to Methodological Standards in Research Using the National Inpatient Sample. JAMA. 2017; 318(20): 2011-2018. https://doi.org/10.1001/jama.2017.17653.
9. Deenadayalan V, Olafimihan A, Ganesan V, Kumi D. & Zia M. Impact of protein-energy malnutrition on outcomes of patients with diffuse large B cell lymphoma admitted for inpatient chemotherapy, Baylor University Medical Center Proceedings. 2023; 36(4): 439-442. DOI: 10.1080/08998280.2023.2204285.
10. Park S, Han B, Cho JW. Effect of nutritional status on survival outcome of diffuse large B-cell lymphoma patients treated with rituxi- mab-CHOP. Nutr Cancer. 2014; 66(2): 225-233. doi:10.1080/01635581. 2014.867065.
11. Kim S, Kim S, Park Y, Shin AR, Yeom H. Nutritional Intervention for a Patient with Acute Lymphoblastic Leukemia on Allogeneic Peripheral Blood Stem Cell Transplantation. Clin Nutr Res. 2018; 7(3): 223-228. doi: 10.7762/cnr.2018.7.3.223. Epub 2018 Jul 26. PMID: 30079320; PMCID: PMC6073168.
12. Amiri Khosroshahi R, Barkhordar M, Talebi S. The impact of malnutrition on mortality and complications of hematopoietic stem cell transplantation in patients with acute leukemia. Clin Nutr. 2023; 42(12): 2520-2527. doi: 10.1016/j.clnu.2023.10.018. Epub 2023 Oct 22. PMID: 37925779.
13. Van Cutsem E, Arends J. The causes and consequences of cancerassociated malnutrition. Eur J Oncol Nurs. 2005; 9(2): 51-63. doi: 10.1016/j.ejon.2005.09.007. PMID: 16437758.
14. Malihi Z, Kandiah M, Chan YM, Hosseinzadeh M, Sohanaki Azad M, Zarif Yeganeh M. Nutritional status and quality of life in patients with acute leukaemia prior to and after induction chemotherapy in three hospitals in Tehran, Iran: a prospective study. J Hum Nutr Diet. 2013;26(1):123-31. doi: 10.1111/jhn.12043. Epub 2013 Apr 30. PMID: 23627676.
15. Lim SL, Ong KC, Chan YH, Loke WC, Ferguson M, Daniels L. Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality. Clin Nutr. 2012; 31(3): 345-50. doi: 10.1016/j.clnu.2011.11.001. Epub 2011 Nov 26. PMID: 22122869.
16. Inciong JFB, Chaudhary A, Hsu HS. Economic burden of hospital malnutrition: A cost-of-illness model. Clin Nutr ESPEN. 2022; 48 :342-350. doi: 10.1016/j.clnesp.2022.01.020. Epub 2022 Jan 22. PMID: 35331511.