Decreased body mass index is associated with poor prognosis in patients with multiple myeloma

Jung, Sung‐Hoon; Yang, Deok‐Hwan; Ahn, Jae‐Sook; Lee, Seung-Shin; Ahn, Seo‐Yeon; Kim, Yeo-Kyeoung; Kim, HyeoungJoon; Lee, Je‐Jung

doi:10.1007/s00277-013-1977-9

Cited by 18 publications

(17 citation statements)

References 27 publications

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“…In addition, low BMI (< 20 kg/m 2 ) was significantly associated with EM, and 27.1 % of patients with low BMI died within 12 months of diagnosis. We previously reported that a low BMI (< 20 kg/m 2 ) at the time of diagnosis was associated with poor survival [ 26 ]. Low BMI may reflect involuntary weight loss caused principally by cancer-associated cachexia [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

Risk factors associated with early mortality in patients with multiple myeloma who were treated upfront with a novel agents containing regimen

et al. 2016

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BackgroundAlthough the introduction of novel agents improved the survival outcomes in patients with multiple myeloma (MM), some patients died within one year (early mortality, EM) following diagnosis. In this study, we evaluated the EM rate, and investigated the risk factors associated with EM in MM patients.MethodsRetrospective data from 542 patients who were initially treated with a novel agent-containing regimen were analyzed.ResultsThe median overall survival (OS) for the entire cohort was 56.5 months. The median OS in the 2010–2014 group was longer than in the 2002–2009 group (59.2 months vs. 49.1 months, P = 0.054). The rate of EM was 13.8 %, and the most common causes of EM were infection and comorbidity. In multivariate analysis, the age-adjusted Charlson comorbidity index (ACCI ≥ 4), low body mass index (BMI < 20 kg/m2), thrombocytopenia, and renal failure were significantly associated with EM. The presence of none, 1, or ≥ 2 factors was associated with a 4.1 %, 14.3 %, or 27.4 % risk of EM (P < 0.001), respectively. The median OS times were significantly different depending on the presence of factors associated with EM (P < 0.001).ConclusionsIn conclusion, the ACCI (≥ 4), low BMI, thrombocytopenia and renal failure were strong predictors for EM in the novel agent era. The results of this study will help to identify patients at high risk for EM, and may be helpful to more accurately predict prognosis of MM patients in the novel-agent era.

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Section: Discussionmentioning

confidence: 99%

Risk factors associated with early mortality in patients with multiple myeloma who were treated upfront with a novel agents containing regimen

et al. 2016

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“…BMI can be considered a surrogate marker of cancer severity because low body weight often is associated with more advanced cancer. Previous studies showed an association of BMI with survival in patients with cancer [18,23]. Furthermore, we divided multiple bone metastases into those with and those without spinal involvement and visceral metastases into lung and/or liver metastases and brain metastases to explore differences in their association with survival.…”

Section: Discussionmentioning

confidence: 99%

2015 Marshall Urist Young Investigator Award: Prognostication in Patients With Long Bone Metastases: Does a Boosting Algorithm Improve Survival Estimates?

Janssen

Heijden

Dijke

et al. 2015

Clin Orthop Relat Res

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Background Survival estimation guides surgical decisionmaking in metastatic bone disease. Traditionally, classic scoring systems, such as the Bauer score, provide survival estimates based on a summary score of prognostic factors. Identification of new factors might improve the accuracy of these models. Additionally, the use of different algorithms-nomograms or boosting algorithms-could further improve accuracy of prognostication relative to classic scoring systems. A nomogram is an extension of a classic scoring system and generates a more-individualized survival probability based on a patient's set of characteristics using a figure. Boosting is a method that automatically trains to classify outcomes by applying classifiers (variables) in a sequential way and subsequently combines them. A boosting algorithm provides survival probabilities based on every possible combination of variables. Questions/purposes We wished to (1) assess factors independently associated with decreased survival in patients with metastatic long bone fractures and (2) compare the accuracy of a classic scoring system, nomogram, and boosting algorithms in predicting 30-, 90-, and 365-day survival. Methods We included all 927 patients in our retrospective study who underwent surgery for a metastatic long bone fracture at two institutions between January 1999 and December 2013. We included only the first procedure if patients underwent multiple surgical procedures or had more than one fracture. Median followup was 8 months (interquartile range, 3-25 months); 369 of 412 (90%) patients who where alive at 1 year were still in followup. Multivariable Cox regression analysis was used to identify One author (SJ) certifies that he has received, an amount less than USD 10,000, from the Anna Foundation (Oegstgeest, The Netherlands), an amount less than USD 10,000 from the De Drie Lichten Foundation (Hilversum, The Netherlands), an amount less than USD 10,000 from the KWF Kankerbestrijding (Amsterdam, The Netherlands), and an amount less than USD 10,000, from the Michael van Vloten Foundation (Rotterdam, The Netherlands). One author (JS) certifies that he or a member of his family has or may receive payments or benefits, an amount less than USD 10,000, from Stryker (Kalamazoo, MI, USA), and an amount less than USD 10,000, from Biom'up (Saint-Priest, Lyon, France). All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research 1 editors and board members are on file with the publication and can be viewed on request. Each author certifies that his or her institution approved the human protocol for this investigation, that all investigations were conducted in conformity with ethical principles of research. This work was performed at Massachusetts General Hospital, Boston, MA, USA. clinical and laboratory factors independently associated with decreased survival. We created a classic scoring system, nomogram, and boosting algorithms based on identified variables. Accuracy of the algorithms was assessed using area unde...

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“…Most included studies defined undernutrition or malnutrition as BMI <18.5 kg/m 2 , and in 1 study Jung 13 used BMI <20 kg/m 2 as the low BMI cut point (Table 1). Of the 23 included studies, 16 had clinical outcomes including mortality and/or complications all using BMI <18.5 kg/m 2 as low BMI cut point.…”

Section: Prevalence Of Low Bmi In Asian Patientsmentioning

confidence: 99%

“…20 In Chinese cancer patients, the prevalence of BMI <18.5 ranged from 9% to 16% (9% in 230 urinary cancer patients 21 ; 10% in 400 nasopharyngeal cancer patients 22 ; 13% in 1248 gastric cancer patients 5 ; and 16% in 2031 esophageal cancer patients 6 ). Studies from South Korean clinics reported prevalence of low BMI from 3% to 12% (3% in 2030 renal cell cancer patients 23,24 ; 5% in 562 diffuse large B-cell lymphoma patients 25 ; and 12% in 193 multiple myeloma patients 13 ). And in South Korean ICU patients, 12% of 3655 patients 26 and 17% in 471 ICU patients 27 had BMI <18.5 kg/m 2 .…”

Section: Prevalence Of Low Bmi In Asian Patientsmentioning

confidence: 99%

Does Low Body Mass Index Predict Mortality in Asian Hospitalized Patients?

Xue

Higashikuchi

et al. 2019

J Parenter Enteral Nutr

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Background: Studies on malnutrition suggest low body mass index (BMI) may be associated with poor clinical outcomes. We investigated published data to identify whether low BMI could predict short-term and long-term clinical outcomes in Asian hospitalized patients. Methods: A search was conducted in the PubMed database including terms "body mass index" or "BMI" or "malnutrition" or "undernutrition" AND "Asia" or "Asian" AND "outcome" or "complication" or "mortality" or "survival" or "ICU" for publications in English in the past 10 years. Papers with data and clinical outcomes from Asian hospitalized patients with BMI <18.5 kg/m 2 and sample size >50 were included. Forest plots were constructed to determine the odds of hospital complications, hospital mortality, intensive care unit (ICU) mortality, and 5-year mortality in patients with BMI <18.5 kg/m 2 vs BMI ࣙ18.5 kg/m 2. Results: Twenty-three studies were included, 16 of which were analyzed for the association between low BMI and clinical outcomes. The prevalence of BMI <18.5 kg/m 2 varied from 3% to 48% in different disease settings and Asian areas. Patients with BMI <18.5 kg/m 2 had significantly higher ICU mortality (odds ratio [OR], 1.92; 95% CI, 1.84-2.01), higher hospital mortality (OR, 2.48; 95% CI, 2.42-2.55), and higher 5-year mortality (OR, 2.74; 95% CI, 2.08-3.63). Complications during hospital stay were significantly higher in patients with BMI <18.5 kg/m 2 (OR, 1.99; 95% CI, 1.65-2.40). Conclusions: Low BMI defined as <18.5 kg/m 2 may predict worse short-term and longer-term outcomes in Asian hospitalized patients.

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Decreased body mass index is associated with poor prognosis in patients with multiple myeloma

Cited by 18 publications

References 27 publications

Risk factors associated with early mortality in patients with multiple myeloma who were treated upfront with a novel agents containing regimen

Risk factors associated with early mortality in patients with multiple myeloma who were treated upfront with a novel agents containing regimen

2015 Marshall Urist Young Investigator Award: Prognostication in Patients With Long Bone Metastases: Does a Boosting Algorithm Improve Survival Estimates?

Does Low Body Mass Index Predict Mortality in Asian Hospitalized Patients?

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