Does the “obesity paradox” really exist in lung cancer surgery? —maybe we should recognize what is the “obesity” first
Editorial

Does the “obesity paradox” really exist in lung cancer surgery? —maybe we should recognize what is the “obesity” first

Shuangjiang Li1,2, Guowei Che1, Lunxu Liu1, Longqi Chen1

1Department of Thoracic Surgery, 2State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China

Correspondence to: Shuangjiang Li. Department of Thoracic Surgery/State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Guoxue Alley No. 37, Chengdu 610041, China. Email: shuangjiang_li@foxmail.com; Guowei Che. Department of Thoracic Surgery, West China Hospital, Sichuan University, Guoxue Alley No. 37, Chengdu 610041, China. Email: guowei_che@foxmail.com.

Provenance: This is an invited Editorial commissioned by the Section Editor Shuangjiang Li (Department of Thoracic Surgery and West China Medical Center, West China Hospital, Sichuan University, Chengdu, China).

Comment on: Sepesi B, Gold KA, Correa AM, et al. The Influence of Body Mass Index on Overall Survival Following Surgical Resection of Non-Small Cell Lung Cancer. J Thorac Oncol 2017;12:1280-7.

Submitted Oct 26, 2018. Accepted for publication Jan 05, 2019.

doi: 10.21037/jtd.2019.01.34

Although there are many other measures for subject body composition, the body mass index (BMI), calculated by the total weight divided by the square of height, has been widely accepted as a universal tool for the patient health risk assessment. A dramatic increase in baseline BMI has been reported to show a definitive correlation to a range of metabolic, cardiovascular, and malignant diseases (1,2). Current evidence demonstrates that the patients with BMI ≥30 kg/m2, who are generally considered as the ‘obese’ patients in routine clinical practice, may have both significantly higher morbidity and mortality rates after elective surgery, especially after cardiac operations (3,4). However, it seems that such “obese” patients may have a lower mortality rate after lung cancer surgery (3).

In the latest evidenced-based review conducted by our research team, we synthesized the outcome data from 25 eligible cohort studies and further identified a paradoxical benefit of the “obesity” (defined by BMI ≥30 kg/m2) for overall morbidity, in-hospital mortality and long-term survival in patients undergoing lung cancer surgery (5). The favorable effects of per unit increase in BMI and the obesity defined by BMI ≥30 kg/m2 were also supported by the most recent large-scale single-center retrospective analysis conducted by Dr. Boris Sepesi with his colleagues from the University of Texas MD Anderson Cancer Center (6). In Dr. Sepesi’s study, the authors reviewed the survival data of 1,935 surgical patients with non-small cell lung cancer (NSCLC) during a 15-year period and found:

  • Per unit increase in BMI remained an independent prognostic factor for overall survival (OS) in both univariable (P<0.01) and multivariable (P=0.02) Cox regression analyses;
  • “Morbidly obese” patients (BMI ≥35 kg/m2) had a tendency towards better OS than that of “obese” patients (BMI ≥30 but <35 kg/m2: P=0.05), overweight patients (BMI ≥25 but <30 kg/m2: P=0.13) and normally weight patients (BMI ≥18.5 but <25 kg/m2: P=0.37);
  • Propensity score matching analysis demonstrated that the patients with BMI ≥30 kg/m2 had a significantly better OS than that of patients with BMI ranged 18.5–25 kg/m2.

Dr. Sepesi with his colleagues further analyzed the available data from The Cancer Genome Atlas (TCGA) dataset and sought to investigate the genetic connection behind the association between a high level of BMI and improved OS of NSCLC. The authors found that the overexpression of uncoupling protein 2 (UCP2), a member of the mitochondrial uncoupling protein family with the function to suppress the production of mitochondrial reactive oxygen species, promote the fatty acid oxidation and limit the utilization of glycolysis-induced pyruvate, was significantly associated with better postoperative OS (6,7). This TCGA dataset analysis might support the most recent laboratory evidence indicating that the upregulation of UCP2 might play a key role to inhibit the proliferation of cancer cells by regulating the cellular metabolism (8).

Both of above findings from current high-quality investigations seem to support that the “obesity paradox”, a new phenomenon showing favorable and protective effects of the clinically diagnosed obesity (BMI ≥30 kg/m2), may really exist in lung cancer surgery (5,6,9). We have tried to explain the possible reasons underlying the “obesity paradox” in our systematic review with meta-analysis (5). We hypothesized that these “obese” patients with operable NSCLC might have a younger age and more peripheral adipose tissue, receive a more regular and intensive medical treatment, and own a better ability to store nutrients to resist surgical interventions compared with the normal/underweight patients (5). Although there is some truth in all of these possible mechanisms, they still remain speculative.

However, Dr. Katherine Flegal with her colleague recently recommended that we should abandon the application of the term “obesity paradox” since the term “obesity paradox” was a figure of speech, not a scientific term with a precise definition (10). Dr. Flegal thinks that the “obesity paradox” terminology is essentially a rhetorical device in which the researchers collect a range of current studies together and further identify a unitary phenomenon showing an unexpected benefit of clinically diagnosed obesity (BMI ≥30 kg/m2). Such findings can be easily influenced by a variety of confounding factors that may differ across diseases and treatments, and are not necessarily mutually exclusive, such as the selection bias from the retrospective nature (11), undetected cachexia (12), weight loss induced by chronic wasting diseases before surgery (13), and lower likelihood of receiving guideline-recommended treatments (14). The “obesity paradox” terminology oversimplifies a complex of underlying pathophysiological mechanisms. Dr. Flegal further indicates that more worrying is the misleading information conveyed by clinical investigations stating the concept of the “obesity paradox” to the general public (10). Therefore, the simplest way to avoid the wrong message to general population, which suggests that “the obesity may be favorable”, is just to describe the patterns of association between different levels of BMI and clinical outcomes rather than to inculcate the term “obesity paradox” in the future (10).

In our systematic review, we had ever hypothesized one plausible reason indicating that being obese might not be protective but being underweight had a significant relationship with worse postoperative outcomes (5). In Dr. Sepesi’s study, the authors carried out a propensity score matching analysis based on 464 well-matched pairs of surgical patients, and then compared the OS between two groups of patients with BMI <25 kg/m2 (normal/underweight) and with BMI ≥25 kg/m2 (overweight/obese). They found that the patients with BMI <25 kg/m2 had a significantly worse prognosis than that of patients with BMI ≥30 kg/m2 (obese) and with BMI ≥35 kg/m2 (morbidly obese). Furthermore, the patients with BMI <18.5 kg/m2 (underweight) seemed to have similar outcomes to those of patients with BMI ranged 20–25 kg/m2 (normal). To our knowledge, abundant evidence demonstrates that the underweight state defined by BMI <18.5 kg/m2, which can represent a seriously declined nutritional reserve, serves as a potent prognostic factor for poor surgical outcomes (15-17). As we previously reported, these findings may create an illusion that the “obesity” state, which is generally identified by BMI ≥30 kg/m2, has a paradoxical benefit in surgical populations (5). We tend to agree with Dr. Flegal’s opinions suggesting that it may be more appropriate to study the “normal weight paradox”, instead of the “obesity paradox”, to find why normal weight isn’t associated with favorable survival in surgical populations (10).

The major concern that urges us to re-examine the “obesity paradox” in lung cancer surgery is the measurement of “obesity”. Essentially, obesity is a body composition disorder defined by relative or absolute excess of body fat (18). Abundant evidence demonstrates that excess adiposity is characterized by a deteriorated physiological state due to alterations in the insulin metabolism (insulin resistance), sexual hormone levels, activation of growth factor signaling, induction of special lipids, and secretion of inflammatory cytokines, such as the tumor necrosis factor-α and interleukin-6 (19-21). Evidence from the latest molecular studies also support that excess adiposity plays a pivotal role in controlling cellular growth, proliferation and cancer progression by activating the mammalian target of rapamycin (mTOR) pathway, and in regulating essential metabolic processes through reactive oxygen species (22). Therefore, the obesity-induced metabolic disruptions can contribute to create a favorable environment for tumorigenesis and cancer progression (23). Given such concerns, it will be easily understood that the “obesity” state, which follows the nature of “an excess of body fat”, is hypothesized to worse the prognosis after a cancer diagnosis.

However, in the majority of current epidemiological studies and clinical trials, the baseline BMI, an objective, simple and convenient method, is still utilized as the most common surrogate measure for obesity (24). Actually, BMI usually fails to provide accurate information on subject body composition due to its major limitation in distinguishing between lean body mass (including skeletal muscle, organs, bone, and connective tissue) and fat body mass (25). Evidence from imaging reports indicates that there can be substantial variation in the amount and distribution between muscular tissue and adipose tissue among cancer patients with identical BMIs (26). The performance of BMI to diagnose excess adiposity has a high specificity but really low sensitivity, resulting in the failure of accurate obesity detection (27). Applying BMI alone may overestimate the “obesity” in the individuals with abundant muscular mass or with volume overload, but conversely, underestimate the “obesity” in the elderly people and the cancer patients who tend to suffer from progressive wasting of lean body mass as well as abundance of adiposity due to malignant behaviors (27-29). This major limitation also makes the BMI fail to provide a sufficient sensitivity to measure the adiposity across ethnically diverse populations among whom there is profound variation in body composition (26,27).

Another imperfection of BMI as a surrogate measure for excess adiposity is that BMI fails to differentiate the regional distribution of fat (26,30). It has been recognized that the susceptibility to suffer from obesity-induced metabolic complications is not essentially mediated by total body fat mass, but is strongly dependent on the body fat distribution and the ability of subcutaneous adipose tissue to sufficiently expand when necessary (30-33). The validity of BMI to identify the “obese” patients will be largely attenuated since BMI cannot satisfy the physicians to distinguish between adipose tissue components (i.e., visceral, subcutaneous, intermuscular, and intramuscular) (26).

Given above limitations of BMI for measuring obesity or distinguishing between diverse body composition components, we suggest that it may be more reasonable to regard BMI as a rough proxy to assess lean body mass, because the baseline BMI itself mainly reflects total body weight rather than fat body weight, and the lean body mass takes up approximately 75–90% of total body weight in normal adults. On the contrary, regarding BMI as a proxy for adiposity has a great probability of exposure misclassification, resulting in a large decline of evidence power for associations with clinical outcomes (27). Therefore, we recommend thoracic surgeons to utilize the clinically routine computed tomography scans or other effective biomedical imaging methods (i.e., dual-energy X-ray absorptiometry and bioelectrical impedance analysis), rather than just to calculate the simple BMI, to provide precise estimates of both muscle and adipose tissues, because the precise quantification of fat body mass and lean body mass has broad implications for personalized cancer care, including the tailored lifestyle interventions, risk stratification for surgery and neoadjuvant/adjuvant chemotherapy dosing (26,34,35).

Given above reviews, we finally advocate what Dr. Cespedes with her colleagues recently recommended that it may be more appropriate to use the term “BMI paradox”, instead of the term “obesity paradox”, to indicate the better survival outcomes in the cancer patients with a higher level of BMI (26). It will be extremely important to recognize whether “a higher BMI” or “excess adiposity” is protective or harmful for malignancy prognosis first. Then, on the basis of accurate assessment of body composition, we will be able to develop the evidence-based guidelines and further design appropriate therapeutic options to promote the health and longevity of cancer survivors (26).

In summary, we think that we need to recognize which patients should be considered as “obese” first when discussing whether the “obesity paradox” really exists in lung cancer surgery. The “obesity” defined by BMI alone may fail to provide a precise estimate of body fat mass due to major limitations of BMI for distinguishing between body composition components and for differentiating body fat distribution. We should not deny that a higher level of BMI may be significantly associated with more favorable survival of operable NSCLC. However, the potential of “obesity paradox” in lung cancer surgery needs to be re-examined through the independent prognostic significance of both adipose and muscular tissues rather than of the BMI only.

Acknowledgements

We thank Mr. Stanley Crawford, from the Institution of Medical English, West China Medical Center, Sichuan University, Chengdu, China, for her help with the English language editing of this editorial manuscript.

Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.

References

  1. Prospective Studies Collaboration, Whitlock G, Lewington S, et al. Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies. Lancet 2009;373:1083-96. [Crossref] [PubMed]
  2. Renehan AG, Tyson M, Egger M. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet 2008;371:569-78. [Crossref] [PubMed]
  3. Dindo D, Muller MK, Weber M, et al. Obesity in general elective surgery. Lancet 2003;361:2032-5. [Crossref] [PubMed]
  4. Phan K, Khuong JN, Xu J, et al. Obesity and postoperative atrial fibrillation in patients undergoing cardiac surgery: Systematic review and meta-analysis. Int J Cardiol 2016;217:49-57. [Crossref] [PubMed]
  5. Li S, Wang Z, Huang J, et al. Systematic review of prognostic roles of body mass index for patients undergoing lung cancer surgery: does the 'obesity paradox' really exist? Eur J Cardiothorac Surg 2017;51:817-28. [PubMed]
  6. Sepesi B, Gold KA, Correa AM, et al. The Influence of Body Mass Index on Overall Survival Following Surgical Resection of Non-Small Cell Lung Cancer. J Thorac Oncol 2017;12:1280-7. [Crossref] [PubMed]
  7. Pecqueur C, Bui T, Gelly C, et al. Uncoupling protein-2 controls proliferation by promoting fatty acid oxidation and limiting glycolysis-derived pyruvate utilization. FASEB J 2008;22:9-18. [Crossref] [PubMed]
  8. Esteves P, Pecqueur C, Alves-Guerra MC. UCP2 induces metabolic reprogramming to inhibit proliferation of cancer cells. Mol Cell Oncol 2014;2:e975024. [Crossref] [PubMed]
  9. Valentijn TM, Galal W, Tjeertes EK, et al. The obesity paradox in the surgical population. Surgeon 2013;11:169-76. [Crossref] [PubMed]
  10. Flegal KM, Ioannidis JPA. The Obesity Paradox: A Misleading Term That Should Be Abandoned. Obesity (Silver Spring) 2018;26:629-30. [Crossref] [PubMed]
  11. Banack HR, Kaufman JS. Does selection bias explain the obesity paradox among individuals with cardiovascular disease? Ann Epidemiol 2015;25:342-9. [Crossref] [PubMed]
  12. Brida M, Dimopoulos K, Kempny A, et al. Body mass index in adult congenital heart disease. Heart 2017;103:1250-7. [Crossref] [PubMed]
  13. Pocock SJ, McMurray JJ, Dobson J, et al. Weight loss and mortality risk in patients with chronic heart failure in the candesartan in heart failure: assessment of reduction in mortality and morbidity (CHARM) programme. Eur Heart J 2008;29:2641-50. [Crossref] [PubMed]
  14. Valle JA, O'Donnell CI, Armstrong EJ, et al. Guideline Recommended Medical Therapy for Cardiovascular Diseases in the Obese: Insights From the Veterans Affairs Clinical Assessment, Reporting, and Tracking (CART) Program. J Am Heart Assoc 2016;5. [Crossref] [PubMed]
  15. Matsunaga T, Suzuki K, Imashimizu K, et al. Body Mass Index as a Prognostic Factor in Resected Lung Cancer: Obesity or Underweight, Which Is the Risk Factor? Thorac Cardiovasc Surg 2015;63:551-7. [Crossref] [PubMed]
  16. Win T, Ritchie AJ, Wells FC, et al. The incidence and impact of low body mass index on patients with operable lung cancer. Clin Nutr 2007;26:440-3. [Crossref] [PubMed]
  17. Yang R, Cheung MC, Pedroso FE, et al. Obesity and weight loss at presentation of lung cancer are associated with opposite effects on survival. J Surg Res 2011;170:e75-83. [Crossref] [PubMed]
  18. McTigue KM, Hess R, Ziouras J (Editor). Diagnosis and Treatment of Obesity in the Elderly [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2003 Dec. AHRQ Technology Assessments.
  19. Heymsfield SB, Wadden TA. Mechanisms, Pathophysiology, and Management of Obesity. N Engl J Med 2017;376:254-66. [Crossref] [PubMed]
  20. Pollak M. Insulin and insulin-like growth factor signalling in neoplasia. Nat Rev Cancer 2008;8:915-28. [Crossref] [PubMed]
  21. Trestini I, Carbognin L, Bonaiuto C, et al. The obesity paradox in cancer: clinical insights and perspectives. Eat Weight Disord 2018;23:185-93. [Crossref] [PubMed]
  22. Leslie NR. The redox regulation of PI 3-kinase-dependent signaling. Antioxid Redox Signal 2006;8:1765-74. [Crossref] [PubMed]
  23. Lohmann AE, Goodwin PJ, Chlebowski RT, et al. Association of Obesity-Related Metabolic Disruptions With Cancer Risk and Outcome. J Clin Oncol 2016;34:4249-55. [Crossref] [PubMed]
  24. Park Y, Peterson LL, Colditz GA. The Plausibility of Obesity Paradox in Cancer-Point. Cancer Res 2018;78:1898-903. [Crossref] [PubMed]
  25. Lu Y, Shu H, Zheng Y, et al. Comparison of fat-free mass index and fat mass index in Chinese adults. Eur J Clin Nutr 2012;66:1004-7. [Crossref] [PubMed]
  26. Cespedes Feliciano EM, Kroenke CH, Caan BJ. The Obesity Paradox in Cancer: How Important Is Muscle? Annu Rev Nutr 2018;38:357-79. [Crossref] [PubMed]
  27. Okorodudu DO, Jumean MF, Montori VM, et al. Diagnostic performance of body mass index to identify obesity as defined by body adiposity: a systematic review and meta-analysis. Int J Obes (Lond) 2010;34:791-9. [Crossref] [PubMed]
  28. Cuppari L. Diagnosis of obesity in chronic kidney disease: BMI or body fat? Nephrol Dial Transplant 2013;28 Suppl 4:iv119-21. [Crossref] [PubMed]
  29. Cruz-Jentoft AJ, Landi F, Schneider SM, et al. Prevalence of and interventions for sarcopenia in ageing adults: a systematic review. Report of the International Sarcopenia Initiative (EWGSOP and IWGS). Age Ageing 2014;43:748-59. [Crossref] [PubMed]
  30. Piché ME, Poirier P, Lemieux I, et al. Overview of Epidemiology and Contribution of Obesity and Body Fat Distribution to Cardiovascular Disease: An Update. Prog Cardiovasc Dis 2018;61:103-13. [Crossref] [PubMed]
  31. Neeland IJ, Poirier P, Després JP. Cardiovascular and Metabolic Heterogeneity of Obesity: Clinical Challenges and Implications for Management. Circulation 2018;137:1391-406. [Crossref] [PubMed]
  32. Karpe F, Pinnick KE. Biology of upper-body and lower-body adipose tissue--link to whole-body phenotypes. Nat Rev Endocrinol 2015;11:90-100. [Crossref] [PubMed]
  33. Tchernof A, Després JP. Pathophysiology of human visceral obesity: an update. Physiol Rev 2013;93:359-404. [Crossref] [PubMed]
  34. Suzuki Y, Okamoto T, Fujishita T, et al. Clinical implications of sarcopenia in patients undergoing complete resection for early non-small cell lung cancer. Lung Cancer 2016;101:92-7. [Crossref] [PubMed]
  35. Fintelmann FJ, Troschel FM, Mario J, et al. Thoracic Skeletal Muscle Is Associated With Adverse Outcomes After Lobectomy for Lung Cancer. Ann Thorac Surg 2018;105:1507-15. [Crossref] [PubMed]
Cite this article as: Li S, Che G, Liu L, Chen L. Does the “obesity paradox” really exist in lung cancer surgery? —maybe we should recognize what is the “obesity” first. J Thorac Dis 2019;11(Suppl 3):S291-S295. doi: 10.21037/jtd.2019.01.34

Article Options

Download Citation

Share