Nutritional Indices in Multiple Myeloma: Predicting Pneumonia and Mortality Post-ASCT (2025)

What if the secret to surviving a stem cell transplant for multiple myeloma wasn't just the procedure itself, but something as everyday as your diet and nutrition? That's the intriguing question at the heart of this groundbreaking research, which dives deep into how pre-transplant nutritional markers might—or might not—predict serious risks like pneumonia and even death after treatment. As someone who's navigated the complexities of medical studies, I'm excited to break this down for you in a way that's easy to follow, even if you're new to the world of oncology and transplants. We'll explore the findings step by step, and along the way, I'll highlight some surprising twists that might challenge what you think you know about nutrition's role in health. Stick around—this is the kind of insight that could spark a lively debate!

Assessing Nutritional Markers Before Transplant as Indicators of Pneumonia and Death in Multiple Myeloma Patients Following Autologous Stem Cell Transplants

• Research
• Open Access (accessible via https://www.springernature.com/gp/open-science/about/the-fundamentals-of-open-access-and-open-research)

• Released: November 11, 2025

• Özlem Duvenci Birben¹,

• Derya Yenibertiz¹,

• Esma Sevil Akkurt¹,

• Tahir Darcın²,

• Yadigar Dila Kes¹ &

• Mehmet Sinan Dal²

BMC Pulmonary Medicine (available at https://bmcpulmmed.biomedcentral.com/) volume 25, Article number: 517 (2025) Cite this article

Abstract

Background/aim

Pneumonia stands out as a major contributor to illness and death in the year following an autologous hematopoietic stem cell transplant (ASCT) for patients battling multiple myeloma (MM), a cancer that arises from abnormal plasma cells in the bone marrow. This condition often leads to weakened bones, immune system deficiencies, and other health issues. Nutrition plays a crucial role in recovery after such intense treatments, and our team wondered if certain nutritional assessments could help predict post-transplant complications. Specifically, we investigated the links between the Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) score with the occurrence of pneumonia and survival rates within one year post-transplant.

Materials and methods

We reviewed data from 286 individuals who underwent ASCT due to multiple myeloma diagnoses between 2013 and 2023 at our center. Participants were divided into groups based on whether they experienced pneumonia in the first year after transplant and their survival status after one year. Pre-transplant GNRI, PNI, and CONUT scores were determined using established formulas based on lab results and clinical details gathered before the procedure.

Results

In our analysis, the average GNRI score was 86.14 ± 11.47 for those without pneumonia and 87.98 ± 13.57 for those who developed it, with no notable differences between the groups. Similarly, PNI scores averaged 89.63 ± 7.22 without pneumonia and 88.67 ± 7.73 with pneumonia, and CONUT scores were 2.39 ± 1.68 and 2.20 ± 1.37, respectively—again, no significant variations. The breakdown of CONUT categories also showed no differences in pneumonia rates across groups. When we looked at how these nutritional markers related to one-year survival post-ASCT, none proved to be reliable predictors.

Conclusion

As a pioneering study examining GNRI, PNI, and CONUT in this specific context, our work revealed no clear connection between pre-transplant nutrition and pneumonia or one-year mortality after ASCT in multiple myeloma cases. Interestingly, the immunosuppressive effects of the transplant itself might overshadow any baseline nutritional influences.

Peer Review reports (available at https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-025-03991-5/peer-review)

Introduction

Multiple myeloma (MM) represents a type of blood cancer driven by the unchecked growth of abnormal plasma cells, which can cause bone marrow failure, skeletal damage, and a compromised immune response [1]. For eligible patients, a standard approach involves high-dose chemotherapy paired with autologous stem cell transplantation (ASCT), where a person's own cells are reinfused after treatment to rebuild the immune system [2]. Yet, ASCT comes with a high risk of infections, and pneumonia is often the primary culprit behind early complications and fatalities post-transplant [3, 4].

The onset of pneumonia after ASCT is closely tied to immune function and nutritional health. Protein-calorie malnutrition, for instance, can weaken the body's defenses by impairing barriers like the skin and mucous membranes, reducing the activity of immune cells like phagocytes, and slowing down lymphocyte production—all of which make someone more vulnerable to bacterial, viral, or fungal lung infections [5]. The intensive conditioning regimens in ASCT, including high-dose chemo, prolonged low white blood cell counts, and damage to mucous membranes, further erode these defenses. This raises the possibility that straightforward nutritional evaluations before transplant could offer clues about infection risks.

Recent explorations have spotlighted the predictive power of tools like the Controlling Nutritional Status (CONUT) score, Geriatric Nutritional Risk Index (GNRI), and Prognostic Nutritional Index (PNI) in MM patients preparing for ASCT. For example, in a group of 59 MM patients, higher pre-transplant CONUT scores were linked to slower recovery of neutrophils (a type of white blood cell) and more frequent mouth sores [6]. Lower PNI levels correlate with increased death rates in cases of community-acquired pneumonia [7], and GNRI serves as a useful marker for risks in aspiration pneumonia among seniors [8]. But here's where it gets controversial: Despite these findings, the utility of these markers in forecasting pneumonia and survival after ASCT for MM remains largely uncharted. And this is the part most people miss—could these tools be underestimating the transplant's own overwhelming impact on immunity?

Prognostic frameworks, such as the International Staging System (ISS) and its updated version (R-ISS), gauge survival by factoring in elements like albumin levels, β2-microglobulin, and genetic abnormalities [5, 9, 10]. Since poor nutrition is associated with higher infection chances, worse tolerance to treatment, and poorer outcomes [11], nutritional assessment tools—particularly CONUT—are gaining traction for evaluating status and infection vulnerability [12]. In light of this, our team set out to explore if CONUT, GNRI, and PNI could anticipate post-transplant pneumonia and one-year mortality in MM patients undergoing ASCT.

Materials and methods

This was a retrospective, single-center investigation involving 286 patients who received autologous stem cell transplants for multiple myeloma between 2013 and 2023. We gathered information on their medical histories, co-existing conditions, lab results, chest imaging, CT scans, pathology findings, treatments, and outcomes, all recorded backward from patient records.

Subjects

Autologous hematopoietic stem cells were sourced from the patients themselves through peripheral blood collection at the Department of Hematology, University of Health Sciences, Ankara Oncology Training and Research Hospital in Ankara, Türkiye. No tissues or cells came from vulnerable groups like prisoners.

Pre-transplant assessment and laboratory variables

All lab data for calculating GNRI, PNI, and CONUT were obtained during standard pre-transplant checks, 7–14 days before cell infusion. We avoided using results from right after conditioning or engraftment. Protocols for treatment, supportive care, antibacterial, antiviral, antifungal, and Pneumocystis jirovecii prophylaxis, along with G-CSF growth factor support, were uniform across all patients.

Inclusion criteria for the study

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Patients aged 18 and over diagnosed with multiple myeloma who had undergone autologous stem cell transplantation.

Exclusion criteria for the study

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Individuals under 18 years old.

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Those with more than one type of cancer.

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Patients whose required data couldn't be retrieved from files or digital systems.

Measurements

We evaluated pre-transplant nutrition using three key indices: the Geriatric Nutritional Risk Index (GNRI), Prognostic Nutritional Index (PNI), and Controlling Nutritional Status (CONUT) score. These were computed with standard equations using lab and clinical info from before the transplant.

CONUT is a method to gauge nutrition via blood tests, focusing on serum albumin (Alb), lymphocyte count (T-Lymph), and total cholesterol (T-Cho) [10]. Drops in T-Lymph and T-Cho earn points from 0 to 3, while Alb reductions get 0, 2, 4, or 6 points based on severity. The total score ranges from normal (0–1) to mild malnutrition (2–4), moderate (5–8), and severe (>9). Higher scores indicate worse nutrition.

For beginners, think of these as simple scoring systems: CONUT looks at blood proteins and fats to spot malnutrition early, GNRI considers age-related factors like body weight ratios, and PNI combines albumin with immune cell counts for a quick health snapshot.

PNI involves checking serum albumin and lymphocyte percentages, calculated as: (10 × serum albumin in g/dL) + (0.005 × total lymphocyte count). It's categorized as normal if ≥50, mild malnutrition at 45–50, moderate-to-severe at 40–45, and severe below 40 [10].

GNRI comes from serum albumin and body mass index (BMI), with the formula: GNRI = 14.89 × albumin (g/dL) + 41.7 × (current weight / ideal weight). Groups are: no risk (>98), low risk (92–98), intermediate (82–91), and high risk (<82) [11].

Patients were grouped by pneumonia development within the first year post-transplant and one-year survival.

Statistical analysis

We used IBM SPSS 15.0 for data crunching. Descriptive stats included means ± standard deviations for normal distributions, medians (min–max) for skewed data, and counts (%) for categories. For two-group comparisons, we applied t-tests for means and Mann-Whitney for medians. For more than two groups, ANOVA for means and Kruskal-Wallis for medians. Chi-Square or Fisher’s Exact tested nominal data. Correlations used Pearson for normal data and Spearman otherwise. Significance was set at p < 0.05.

Results

Out of our group, 35 patients (12.2%) developed pneumonia within a year after ASCT. Among non-pneumonia cases, 60.2% were male and 39.8% female, versus 54.3% male and 45.7% female in the pneumonia group—no significant gender gap. However, average transplant age was notably higher in those who got pneumonia (see Table 1 for details).

Full size table (refer to https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-025-03991-5/tables/1)

Pneumonia types broke down with bacterial as the top cause at 48.6% (17 cases), followed by fungal-bacterial mixes in 6 (17.1%), viral in 3 (8.6%), and viral-bacterial combos in 2 (5.7%).

GNRI medians were 86.14 ± 11.47 without pneumonia and 87.98 ± 13.57 with it. PNI stood at 89.63 ± 7.22 and 88.67 ± 7.73, while CONUT was 2.39 ± 1.68 and 2.20 ± 1.37—all without significant differences (Table 2).

Adjusted analyses revealed no links between GNRI, PNI, or CONUT and one-year pneumonia (all p > 0.10), so we didn't pursue multivariable modeling.

Full size table (https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-025-03991-5/tables/2)

CONUT categories showed no variations in pneumonia rates across nutritional levels (χ² = 1.562; p = 0.668) (Table 3).

Full size table (https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-025-03991-5/tables/3)

By one year post-ASCT, 6.6% (19 patients) had passed away, while 93.4% (267) survived. Of the deaths, 10.52% were pneumonia-related (Table 4).

Full size table (https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-025-03991-5/tables/4)

Nutritional markers didn't differ much between survivors and those who died: PNI averaged 91.07 ± 7.83 in decedents vs. 89.40 ± 7.24 in survivors (not significant, Z = 1.003; p = 0.316). GNRI was 90.18 ± 18.27 vs. 86.09 ± 11.13 (Z = 0.258; p = 0.797), and CONUT 3.00 ± 2.00 vs. 2.32 ± 1.61 (Z = 1.763; p = 0.078) (Table 5).

Full size table (https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-025-03991-5/tables/5)

Discussion

MM patients facing ASCT face steep infection risks due to ongoing low neutrophil counts, damaged barriers, and severe immune suppression, with pneumonia leading the charge in post-transplant issues and deaths [13]. Earlier studies tied pre-transplant malnutrition to worse outcomes, like increased infections [4]. Since ASCT is a core therapy, infections—especially pneumonia—remain a big driver of complications and mortality. Pre-transplant nutrition might affect immune recovery and infection chances, so this study checked if PNI, GNRI, and CONUT could forecast pneumonia in MM after ASCT.

Surprisingly, we found no associations, contrasting prior work. This might stem from ASCT's intense immunosuppression drowning out baseline nutrition signals [14, 15]. For instance, one study showed low pre-transplant albumin (below 3.5 g/dL) doubling bacterial pneumonia risk in the first 100 days post-ASCT [16], but our albumin levels didn't vary by pneumonia status.

GNRI, designed for elders, applies to cancer and transplants. A MM study found it predictive of overall survival [17], yet in our data, it didn't connect to one-year mortality or pneumonia, suggesting its value might shift for post-transplant issues.

CONUT's prognostic role in cancers varies, and its place in MM is unclear. Some research linked high CONUT to shorter survival in MM [17], but we saw no tie to one-year mortality. Beyond infections, CONUT might flag non-infectious problems; in those 59 MM patients, higher scores predicted slower neutrophil recovery and more mouth ulcers [6].

A lymphoma study found low GNRI and high CONUT tied to worse outcomes, but PNI not so much [18]. In our MM group, PNI didn't predict one-year mortality. Another analysis of 74 MM patients identified PNI and CONUT as key in elders [19], but not here. Notably, older age at transplant correlated with pneumonia, reinforcing age as a key risk factor and the need for age-tailored care. While nutrition matters, age might trump it in MM outcomes.

Overall, we uncovered no links between pre-transplant nutrition indices and pneumonia or one-year mortality in MM post-ASCT. Factors like immunosuppression shifts, changing labs during conditioning, and post-transplant variables (e.g., immune rebuilding, graft issues, preventive meds) could play bigger roles. Future work should explore combined models for better risk prediction.

Conclusion

To our knowledge, this marks the first comprehensive look at PNI, GNRI, and CONUT's predictive ability for post-transplant pneumonia and one-year mortality in MM patients undergoing ASCT. Our results indicate no associations, possibly due to lab fluctuations during conditioning reducing baseline reliability. This underscores the need for more dynamic markers to enhance risk assessment here.

Data availability

The datasets analyzed are available from the lead author upon request.

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Acknowledgements

We extend gratitude to all participants in this research.

Funding

This work received support from the University of Health Sciences, Ankara Oncology Training and Research Hospital Ethics Committee (No: 2024-05/66).

Author information

Authors and Affiliations

1. Department of Chest Diseases, University of Health Sciences, Ankara Oncology Training and Research Hospital, Ankara, 06300, Türkiye

Ozlem Duvenci Birben, Derya Yenibertiz, Esma Sevil Akkurt & Yadigar Dila Kes

1. Department of Hematology, University of Health Sciences, Ankara Oncology Training and Research Hospital, Ankara, 06300, Türkiye

Tahir Darcın & Mehmet Sinan Dal

Authors

1. Ozlem Duvenci Birben
2. Derya Yenibertiz
3. Esma Sevil Akkurt
4. Tahir Darcın
5. Yadigar Dila Kes
6. Mehmet Sinan Dal

Contributions

D.Y, E.S.A. and O.D.B. designed the study and drafted the text; D.K, T.D and O.D.B. handled data collection, analysis, and interpretation. O.D.B., E.S.A. and M.S.D. led the writing; all reviewed the final version.

Corresponding author

Correspondence to Esma Sevil Akkurt.

Ethics declarations

Ethics approval and consent to participate

Approved by the University of Health Sciences, Ankara Oncology Training and Research Hospital Ethics Committee (No: 2024-05/66). Informed consent was secured from all before participation. Conducted per the 2013 Helsinki Declaration.

Competing interests

No conflicts declared.

Conflict of interest

None.

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Duvenci Birben, O., Yenibertiz, D., Akkurt, E.S. et al. Evaluating pre-transplant nutritional indices as predictors of pneumonia and mortality in multiple myeloma patients post-autologous stem cell transplantation. BMC Pulm Med 25, 517 (2025). https://doi.org/10.1186/s12890-025-03991-5

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Received: 15 August 2025
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Accepted: 15 October 2025
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Published: 11 November 2025
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Version of record: 11 November 2025
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DOI: https://doi.org/10.1186/s12890-025-03991-5

Keywords

But wait, does this mean we should ignore nutrition altogether in transplant prep? Or could there be hidden factors at play that future studies might uncover? What are your thoughts on balancing age, immunity, and nutrition in cancer care? Do you agree that the transplant process itself might be the real game-changer, overshadowing these markers? Let's hear from you in the comments—your insights could spark some real discussion!