Kanser Hastalarında Beslenme Durumu ve Vücut Kompozisyonu Değerlendirmesi
Özet
Kanser, doğrudan etkileri ve neden olduğu metabolik bozukluklar nedeniyle beslenme durumunu olumsuz etkiler ve malnütrisyon riskini ciddi ölçüde artırır. Literatürde, kanserle ilişkili ölümlerin genelde %10-20’sinin malnütrisyona bağlı olduğu belirtilirken, bazı kaynaklarda bu oranın %40’a kadar çıkabildiği rapor edilmiştir. Malnütrisyon, inflamasyon, metabolik adaptasyonlar ve sistemik süreçlerin bir araya gelmesiyle ortaya çıkar; yalnızca kilo ve kas kaybına neden olmakla kalmaz, aynı zamanda geri dönüşü olmayan kaşeksi gibi ağır klinik tabloların gelişimine zemin hazırlar. Bu nedenle, kanser hastalarında malnütrisyonun erken teşhisi ve GLIM kriterleri gibi standardize yaklaşımlar doğrultusunda multidisipliner bir izlem planının oluşturulması, tedavi sonuçlarının iyileştirilmesi için kritik öneme sahiptir.
Malnütrisyonun doğru bir şekilde değerlendirilebilmesi, risk altındaki bireylerin erken tanısını sağlayabilen yüksek duyarlılığa sahip tarama araçlarının kullanımını gerektirir. Bu bağlamda, klinik pratiğe yön veren ve ESPEN tarafından önerilen NRS-2002, MUST ve MNA, sık kullanılan tarama araçları arasında yer alır. Ayrıca, MNA ve PG-SGA gibi kapsamlı değerlendirme yöntemleri, yalnızca beslenme durumunu analiz etmekle kalmaz, bireyselleştirilmiş tedavi planlarının oluşturulmasında kritik bir rehber sağlar. Bunun yanı sıra, CRP, albümin ve prealbumin gibi biyobelirteçlerin yanı sıra, BIA, DEXA, BT ve MR gibi modern ölçüm teknikleri, beslenme durumunun detaylı bir şekilde değerlendirilmesini ve tedaviye verilen yanıtın izlenmesini sağlar.
Kanserle ilişkili anoreksi, kaşeksi ve sarkopeni gibi durumlar, yalnızca beslenme desteğinin etkinliği açısından değil, onkolojik tedavi süreçlerinin genel başarısı için de kritik öneme sahiptir. Unutulmamalıdır ki, malnütrisyon yönetimi olmaksızın kanser tedavisinde kalıcı başarı mümkün değildir. Beslenme odaklı yaklaşımlar, standart tedavi paradigmasının ayrılmaz bir parçasıdır.
Cancer adversely affects nutritional status due to its direct effects and the metabolic disorders it causes, significantly increasing the risk of malnutrition. While the literature indicates that 10–20% of cancer-related deaths are generally attributed to malnutrition, some sources report this rate as high as 40%. Malnutrition arises from a combination of inflammation, metabolic adaptations, and systemic processes; it not only leads to weight and muscle loss but also paves the way for severe clinical conditions such as irreversible cachexia. Therefore, the early diagnosis of malnutrition in cancer patients and the creation of a multidisciplinary monitoring plan in line with standardized approaches like the GLIM criteria are critical for improving treatment outcomes.
Accurate assessment of malnutrition requires the use of screening tools with high sensitivity that can enable the early identification of individuals at risk. In this context, screening tools commonly used in clinical practice and recommended by ESPEN, such as NRS-2002, MUST, and MNA, play a pivotal role. Additionally, comprehensive evaluation methods like MNA and PG-SGA not only analyze nutritional status but also provide critical guidance for the creation of individualized treatment plans. Moreover, biomarkers such as CRP, albumin, and prealbumin, alongside advanced measurement techniques like BIA, DEXA, CT, and MRI, facilitate a detailed evaluation of nutritional status and enable the monitoring of responses to treatment.
Conditions such as cancer-related anorexia, cachexia, and sarcopenia are crucial not only for the efficacy of nutritional support but also for the overall success of oncological treatment processes. It should not be forgotten that lasting success in cancer treatment is impossible without the management of malnutrition. Nutrition-focused approaches are an integral part of the standard treatment paradigm.
Referanslar
Pressoir M, Desné S, Berchery D, et al. Prevalence, risk factors and clinical implications of malnutrition in French Comprehensive Cancer Centres. Br J Cancer. 2010;102(6):966–71.
Sesterhenn AM, Szalay A, Zimmermann AP, et al. [Significance of autopsy in patients with head and neck cancer]. Laryngorhinootologie. 2012;91(6):375–80.
Patrick Quillin, Beating Cancer with Nutrition (Nutrition Times Press, Inc. 2005).
Hébuterne X, Lemarié E, Michallet M, et al. Prevalence of malnutrition and current use of nutrition support in patients with cancer. JPEN J Parenter Enteral Nutr. 2014;38(2):196–204.
Planas M, Álvarez-Hernández J, León-Sanz M, et al. Prevalence of hospital malnutrition in cancer patients: a sub-analysis of the PREDyCES® study. Support Care Cancer. 2016;24(1):429–35.
Korfali G, Gündoğdu H, Aydintuğ S, et al. Nutritional risk of hospitalized patients in Turkey. Clin Nutr. 2009;28(5):533–7.
Attar A, Malka D, Sabaté JM, et al. Malnutrition is high and underestimated during chemotherapy in gastrointestinal cancer: an AGEO prospective cross-sectional multicenter study. Nutr Cancer. 2012;64(4):535–42.
Gyan E, Raynard B, Durand JP, et al. Malnutrition in Patients With Cancer: Comparison of Perceptions by Patients, Relatives, and Physicians—Results of the NutriCancer2012 Study. JPEN J Parenter Enteral Nutr. 2018;42(1):255–60.
Arends J, Bachmann P, Baracos V, et al. ESPEN guidelines on nutrition in cancer patients. Clin Nutr. 2017;36(1):11–48.
Jensen GL, Mirtallo J, Compher C, et al. Adult starvation and disease-related malnutrition: a proposal for etiology-based diagnosis in the clinical practice setting from the International Consensus Guideline Committee. JPEN J Parenter Enteral Nutr. 2010;34(2):156–9.
Muscaritoli M, Anker SD, Argilés J, et al. Consensus definition of sarcopenia, cachexia and pre-cachexia: joint document elaborated by Special Interest Groups (SIG) "cachexia-anorexia in chronic wasting diseases" and "nutrition in geriatrics". Clin Nutr. 2010;29(2):154–9.
Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16–31.
Cederholm T, Barazzoni R, Austin P, et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin Nutr. 2017;36(1):49–64.
Prado CM, Cushen SJ, Orsso CE, et al. Sarcopenia and cachexia in the era of obesity: clinical and nutritional impact. Proc Nutr Soc. 2016;75(2):188–98.
Ryan AM, Power DG, Daly L, et al. Cancer-associated malnutrition, cachexia and sarcopenia: the skeleton in the hospital closet 40 years later. Proc Nutr Soc. 2016;75(2):199–211.
Ravasco P. Nutrition in Cancer Patients. J Clin Med. 2019;8(8).
Caillet P, Liuu E, Raynaud Simon A, et al. Association between cachexia, chemotherapy and outcomes in older cancer patients: A systematic review. Clin Nutr. 2017;36(6):1473–82.
Gioulbasanis I, Martin L, Baracos VE, et al. Nutritional assessment in overweight and obese patients with metastatic cancer: does it make sense? Ann Oncol. 2015;26(1):217–21.
Bossi P, Delrio P, Mascheroni A, et al. The Spectrum of Malnutrition/Cachexia/Sarcopenia in Oncology According to Different Cancer Types and Settings: A Narrative Review. Nutrients. 2021;13(6).
Freijer K, Tan SS, Koopmanschap MA, et al. The economic costs of disease-related malnutrition. Clin Nutr. 2013;32(1):136–41.
Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39 Suppl 1:5–41.
Frankenfield D, Roth-Yousey L, Compher C. Comparison of predictive equations for resting metabolic rate in healthy nonobese and obese adults: a systematic review. J Am Diet Assoc. 2005;105(5):775–89.
Pavlidou E, Papadopoulou SK, Seroglou K, et al. Revised Harris-Benedict Equation: New Human Resting Metabolic Rate Equation. Metabolites. 2023;13(2).
Barcellos PS, Borges N, Torres DPM. Resting energy expenditure in cancer patients: Agreement between predictive equations and indirect calorimetry. Clin Nutr ESPEN. 2021;42:286–91.
Mogensen KM, Malone A, Becker P, et al. Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition Consensus Malnutrition Characteristics: Usability and Association With Outcomes. Nutr Clin Pract. 2019;34(5):657–65.
Kondrup J, Rasmussen HH, Hamberg O, et al. Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials. Clin Nutr. 2003;22(3):321–36.
Skipper A, Ferguson M, Thompson K, et al. Nutrition screening tools: an analysis of the evidence. JPEN J Parenter Enteral Nutr. 2012;36(3):292–8.
Leuenberger M, Kurmann S, Stanga Z. Nutritional screening tools in daily clinical practice: the focus on cancer. Support Care Cancer. 2010;18 Suppl 2:S17–27.
Guerra RS, Fonseca I, Sousa AS, et al. ESPEN diagnostic criteria for malnutrition—A validation study in hospitalized patients. Clin Nutr. 2017;36(5):1326–32.
Isenring E, Elia M. Which screening method is appropriate for older cancer patients at risk for malnutrition? Nutrition. 2015;31(4):594–7.
Boléo-Tomé C, Monteiro-Grillo I, Camilo M, et al. Validation of the Malnutrition Universal Screening Tool (MUST) in cancer. Br J Nutr. 2012;108(2):343–8.
Stratton RJ, King CL, Stroud MA, et al. 'Malnutrition Universal Screening Tool' predicts mortality and length of hospital stay in acutely ill elderly. Br J Nutr. 2006;95(2):325–30.
Bauer JM, Volkert D, Wirth R, et al. [Diagnosing malnutrition in the elderly]. Dtsch Med Wochenschr. 2006;131(5):223–7.
Rubenstein LZ, Harker JO, Salvà A, et al. Screening for undernutrition in geriatric practice: developing the short-form mini-nutritional assessment (MNA-SF). J Gerontol A Biol Sci Med Sci. 2001;56(6):M366–72.
Phillips MB, Foley AL, Barnard R, et al. Nutritional screening in community-dwelling older adults: a systematic literature review. Asia Pac J Clin Nutr. 2010;19(3):440–9.
Ukleja A, Gilbert K, Mogensen KM, et al. Standards for Nutrition Support: Adult Hospitalized Patients. Nutr Clin Pract. 2018;33(6):906–20.
Swan WI, Vivanti A, Hakel-Smith NA, et al. Nutrition Care Process and Model Update: Toward Realizing People-Centered Care and Outcomes Management. J Acad Nutr Diet. 2017;117(12):2003–14.
Correia M. Nutrition Screening vs Nutrition Assessment: What's the Difference? Nutr Clin Pract. 2018;33(1):62–72.
Omran ML, Morley JE. Assessment of protein energy malnutrition in older persons, part I: History, examination, body composition, and screening tools. Nutrition. 2000;16(1):50–63.
Hummell AC, Cummings M. Role of the nutrition-focused physical examination in identifying malnutrition and its effectiveness. Nutr Clin Pract. 2022;37(1):41–9.
Bullock AF, Greenley SL, McKenzie GAG, et al. Relationship between markers of malnutrition and clinical outcomes in older adults with cancer: systematic review, narrative synthesis and meta-analysis. Eur J Clin Nutr. 2020;74(11):1519–35.
Cederholm T, Bosaeus I, Barazzoni R, et al. Diagnostic criteria for malnutrition - An ESPEN Consensus Statement. Clin Nutr. 2015;34(3):335–40.
Hamada Y. Objective Data Assessment (ODA) Methods as Nutritional Assessment Tools. J Med Invest. 2015;62(3-4):119–22.
Real GG, Frühauf IR, Sedrez JHK, et al. Calf Circumference: A Marker of Muscle Mass as a Predictor of Hospital Readmission. JPEN J Parenter Enteral Nutr. 2018;42(8):1272–9.
Pinto AC, Sousa AS, Amaral TF, et al. Association Between Anthropometric Indicators of Nutrition Status and Length of Hospital Stay in Hospitalized Patients. JPEN J Parenter Enteral Nutr. 2021;45(2):381–93.
Kyle UG, Bosaeus I, De Lorenzo AD, et al. Bioelectrical impedance analysis--part I: review of principles and methods. Clin Nutr. 2004;23(5):1226–43.
Camina Martín MA, de Mateo Silleras B, Redondo del Río MP. Body composition analysis in older adults with dementia. Anthropometry and bioelectrical impedance analysis: a critical review. Eur J Clin Nutr. 2014;68(11):1228–33.
Cruz-Jentoft AJ, Baeyens JP, Bauer JM, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010;39(4):412–23.
Tosato M, Marzetti E, Cesari M, et al. Measurement of muscle mass in sarcopenia: from imaging to biochemical markers. Aging Clin Exp Res. 2017;29(1):19–27.
Walowski CO, Braun W, Maisch MJ, et al. Reference Values for Skeletal Muscle Mass - Current Concepts and Methodological Considerations. Nutrients. 2020;12(3).
Goodpaster BH, Kelley DE, Wing RR, et al. Effects of weight loss on regional fat distribution and insulin sensitivity in obesity. Diabetes. 1999;48(4):839–47.
Dixon WT. Simple proton spectroscopic imaging. Radiology. 1984;153(1):189–94.
Reeder SB. Emerging quantitative magnetic resonance imaging biomarkers of hepatic steatosis. Hepatology. 2013;58(6):1877–80.
Smith S, Madden AM. Body composition and functional assessment of nutritional status in adults: a narrative review of imaging, impedance, strength and functional techniques. J Hum Nutr Diet. 2016;29(6):714–32.
Sheean P, Gonzalez MC, Prado CM, et al. American Society for Parenteral and Enteral Nutrition Clinical Guidelines: The Validity of Body Composition Assessment in Clinical Populations. JPEN J Parenter Enteral Nutr. 2020;44(1):12–43.
Tillquist M, Kutsogiannis DJ, Wischmeyer PE, et al. Bedside ultrasound is a practical and reliable measurement tool for assessing quadriceps muscle layer thickness. JPEN J Parenter Enteral Nutr. 2014;38(7):886–90.
Strasser EM, Draskovits T, Praschak M, et al. Association between ultrasound measurements of muscle thickness, pennation angle, echogenicity and skeletal muscle strength in the elderly. Age (Dordr). 2013;35(6):2377–88.
Detsky AS, McLaughlin JR, Baker JP, et al. What is subjective global assessment of nutritional status? JPEN J Parenter Enteral Nutr. 1987;11(1):8–13.
White JV, Guenter P, Jensen G, et al. 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 J Parenter Enteral Nutr. 2012;36(3):275–83.
Zhang Z, Pereira SL, Luo M, et al. Evaluation of Blood Biomarkers Associated with Risk of Malnutrition in Older Adults: A Systematic Review and Meta-Analysis. Nutrients. 2017;9(8).
Alajmi A, Almehari A, Alzahrani AR, et al. Impact of Preoperative Serum Albumin Level on the Outcome of Colorectal Cancer Surgery. Cureus. 2024;16(4):e57655.
Keller U. Nutritional Laboratory Markers in Malnutrition. J Clin Med. 2019;8(6).
Erdoğan K, Kara M, Şener FE, et al. Serum albumin as a biomarker of (nutritional status in) sarcopenia. J Bone Miner Metab. 2024.
Cabrerizo S, Cuadras D, Gomez-Busto F, et al. Serum albumin and health in older people: Review and meta analysis. Maturitas. 2015;81(1):17–27.
Chen SH, Zhang BF, Zhang YM. The association between prealbumin concentration at admission and mortality in elderly patients with hip fractures: a cohort study. Arch Osteoporos. 2024;19(1):27.
Dellière S, Cynober L. Is transthyretin a good marker of nutritional status? Clin Nutr. 2017;36(2):364–70.
Férard G, Gaudias J, Bourguignat A, et al. C-reactive protein to transthyretin ratio for the early diagnosis and follow-up of postoperative infection. Clin Chem Lab Med. 2002;40(12):1334–8.
Cynober L. Advances in analytical techniques: from biochemical assessment of nutritional status to the identification of controlling factors. Clin Nutr. 2003;22 Suppl 2:S37–42.
Smith DL. Anemia in the elderly. Am Fam Physician. 2000;62(7):1565–72.
Omran ML, Morley JE. Assessment of protein energy malnutrition in older persons, Part II: Laboratory evaluation. Nutrition. 2000;16(2):131–40.
Buzby GP, Williford WO, Peterson OL, et al. A randomized clinical trial of total parenteral nutrition in malnourished surgical patients: the rationale and impact of previous clinical trials and pilot study on protocol design. Am J Clin Nutr. 1988;47(2 Suppl):357–65.
Cereda E, Pedrolli C. The Geriatric Nutritional Risk Index. Curr Opin Clin Nutr Metab Care. 2009;12(1):1–7.
Lv GY, An L, Sun DW. Geriatric Nutritional Risk Index Predicts Adverse Outcomes in Human Malignancy: A Meta-Analysis. Dis Markers. 2019;2019:4796598.
Rasheedy D, El-Kawaly WH. The accuracy of the Geriatric Nutritional Risk Index in detecting frailty and sarcopenia in hospitalized older adults. Aging Clin Exp Res. 2020;32(12):2469–77.
Mullen JL, Buzby GP, Waldman MT, et al. Prediction of operative morbidity and mortality by preoperative nutritional assessment. Surg Forum. 1979;30:80–2.
Yang Y, Gao P, Chen X, et al. Prognostic significance of preoperative prognostic nutritional index in colorectal cancer: results from a retrospective cohort study and a meta-analysis. Oncotarget. 2016;7(36):58543–52.
Sun K, Chen S, Xu J, et al. The prognostic significance of the prognostic nutritional index in cancer: a systematic review and meta-analysis. J Cancer Res Clin Oncol. 2014;140(9):1537–49.
Onodera T, Goseki N, Kosaki G. [Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients]. Nihon Geka Gakkai Zasshi. 1984;85(9):1001–5.
Ingenbleek Y, Carpentier YA. A prognostic inflammatory and nutritional index scoring critically ill patients. Int J Vitam Nutr Res. 1985;55(1):91–101.
de Ulíbarri Pérez JI, González-Madroño Giménez A, González Pérez P, et al. [New procedure for the early detection and control of hospital malnutrition]. Nutr Hosp. 2002;17(4):179–88.
Kubrak C, Jensen L. Malnutrition in acute care patients: a narrative review. Int J Nurs Stud. 2007;44(6):1036–54.
Håkonsen SJ, Pedersen PU, Bath-Hextall F, et al. Diagnostic test accuracy of nutritional tools used to identify undernutrition in patients with colorectal cancer: a systematic review. JBI Database System Rev Implement Rep. 2015;13(4):141–87.
Ottery FD. Definition of standardized nutritional assessment and interventional pathways in oncology. Nutrition. 1996;12(1 Suppl):S15–9.
Guo W, Ou G, Li X, et al. Screening of the nutritional risk of patients with gastric carcinoma before operation by NRS 2002 and its relationship with postoperative results. J Gastroenterol Hepatol. 2010;25(4):800–3.
Castillo-Martínez L, Castro-Eguiluz D, Copca-Mendoza ET, et al. Nutritional Assessment Tools for the Identification of Malnutrition and Nutritional Risk Associated with Cancer Treatment. Rev Invest Clin. 2018;70(3):121–5.
Cederholm T, Jensen GL, Correia M, et al. GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community. Clin Nutr. 2019;38(1):1–9.
de van der Schueren MAE, Keller H, Cederholm T, et al. Global Leadership Initiative on Malnutrition (GLIM): Guidance on validation of the operational criteria for the diagnosis of protein-energy malnutrition in adults. Clin Nutr. 2020;39(9):2872–80.
Jensen GL, Cederholm T, Correia M, et al. GLIM Criteria for the Diagnosis of Malnutrition: A Consensus Report From the Global Clinical Nutrition Community. JPEN J Parenter Enteral Nutr. 2019;43(1):32–40.
Keller H, de van der Schueren MAE, Jensen GL, et al. Global Leadership Initiative on Malnutrition (GLIM): Guidance on Validation of the Operational Criteria for the Diagnosis of Protein-Energy Malnutrition in Adults. JPEN J Parenter Enteral Nutr. 2020;44(6):992–1003.
Brito JE, Burgel CF, Lima J, et al. GLIM criteria for malnutrition diagnosis of hospitalized patients presents satisfactory criterion validity: A prospective cohort study. Clin Nutr. 2021;40(6):4366–72.
Milanez DSJ, Razzera EL, Lima J, et al. Feasibility and criterion validity of the GLIM criteria in the critically ill: A prospective cohort study. JPEN J Parenter Enteral Nutr. 2023;47(6):754–65.
