Preoperative Inflammatory Markers as a Predictor of Three-Year Overall Survival in Older Cancer Patients Undergoing Oncologic Surgery
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. The PICNIC and PICNIC-B-HAPPY Study
2.2. Patients—Inclusion and Exclusion Criteria
2.3. Blood Sampling and Biochemical Analysis
2.4. Outcomes
2.5. Data Analysis and Statistics
3. Results
3.1. Survival
3.2. Inflammatory Markers—All Included Patients
3.3. Inflammatory Markers—Patients with Colorectal Cancer
4. Discussion
4.1. Evaluation of the Study
4.2. Further Perspectives and Clinical Implementations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix
Tumor Localization | n (%) |
---|---|
Colorectal tumor | 101 (30.8) |
Gastric tumor | 20 (6.1) |
Esophageal tumor | 24 (7.3) |
Small bowel tumor | 9 (2.7) |
Bile duct or gallbladder tumor | 8 (2.4) |
Pancreatic tumor | 14 (4.3) |
Breast tumor | 2 (0.6) |
Thyroid tumor | 15 (4.6) |
Vulvar tumor | 19 (5.8) |
Womb tumor | 15 (4.6) |
Ovarian tumor | 20 (6.1) |
Skin tumor | 42 (12.8) |
Soft tissue | 39 (11.9) |
Comorbidities | n (%) |
---|---|
Myocardial infarction | 16 (4.9%) |
Congestive heart failure | 33 (10.1%) |
Peripheral vascular disease | 76 (23.2%) |
CVA or TIA | 19 (5.8%) |
Dementia | 1 (0.3%) |
COPD | 23 (7.0%) |
Connective tissue disease | 5 (1.5%) |
Peptic ulcer disease | 3 (0.9%) |
Mild liver disease | 1 (0.3%) |
Moderate/severe liver disease | 1 (0.3%) |
Diabetes mellitus | 45 (13.7%) |
Hemiplegia | 1 (0.3%) |
Chronic kidney disease | 6 (1.8%) |
AIDS | 1 (0.3%) |
Disease Stage, (n) | Mean CRP Level in mg/L (SE) |
---|---|
Stage I, (79) | 8.9 (1.6) |
Stage II, (85) | 13.3 (2.7) |
Stage III, (89) | 14.2 (2.8) |
Stage IV, (75) | 14.0 (2.3) |
References
- Ewertz, M.; Christensen, K.; Engholm, G.; Kejs, A.M.T.; Lund, L.; Matzen, L.E.; Pfeiffer, P.; Storm, H.H.; Herrstedt, J.; on behalf of the Academy of Geriatric Cancer Research (AgeCare). Trends in cancer in the elderly population in Denmark, 1980–2012. Acta Oncol. 2016, 55, 1–6. [Google Scholar] [CrossRef] [Green Version]
- Huisman, M.; Audisio, R.; Ugolini, G.; Montroni, I.; Vigano, A.; Spiliotis, J.; Stabilini, C.; Carino, N.D.L.; Farinella, E.; Stanojevic, G.; et al. Screening for predictors of adverse outcome in onco-geriatric surgical patients: A multicenter prospective cohort study. Eur. J. Surg. Oncol. (EJSO) 2015, 41, 844–851. [Google Scholar] [CrossRef] [Green Version]
- Vasto, S.; Candore, G.; Balistreri, C.R.; Caruso, M.; Colonna-Romano, G.; Grimaldi, M.P.; Listi, F.; Nuzzo, D.; Lio, D.; Caruso, C. Inflammatory networks in ageing, age-related diseases and longevity. Mech. Ageing Dev. 2007, 128, 83–91. [Google Scholar] [CrossRef] [PubMed]
- Davalos, A.R.; Coppe, J.-P.; Campisi, J.; Desprez, P.-Y. Senescent cells as a source of inflammatory factors for tumor progression. Cancer Metastasis Rev. 2010, 29, 273–283. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Plas, M.; De Haan, J.J.; Van Der Wal-Huisman, H.; Rutgers, A.; Absalom, A.R.; De Bock, G.H.; Van Leeuwen, B.L. The systemic impact of a surgical procedure in older oncological patients. Eur. J. Surg. Oncol. (EJSO) 2019, 45, 1403–1409. [Google Scholar] [CrossRef] [PubMed]
- Plas, M.; Rutgers, A.; Van Der Wal-Huisman, H.; De Haan, J.J.; Absalom, A.R.; De Bock, G.H.; Van Leeuwen, B.L. The association between the inflammatory response to surgery and postoperative complications in older patients with cancer; a prospective prognostic factor study. J. Geriatr. Oncol. 2020, 11, 873–879. [Google Scholar] [CrossRef] [PubMed]
- Kubota, T.; Hiki, N.; Sano, T.; Nomura, S.; Nunobe, S.; Kumagai, K.; Aikou, S.; Watanabe, R.; Kosuga, T.; Yamaguchi, T. Prognostic Significance of Complications after Curative Surgery for Gastric Cancer. Ann. Surg. Oncol. 2013, 21, 891–898. [Google Scholar] [CrossRef]
- Lin, E.; Calvano, S.E.; Lowry, S.F. Inflammatory cytokines and cell response in surgery. Surgery 2000, 127, 117–126. [Google Scholar] [CrossRef]
- Szaflarska, A.; Szczepanik, A.; Siedlar, M.; Czupryna, A.; Sierzega, M.; Popiela, T.; Zembala, M. Preoperative plasma level of IL-10 but not of proinflammatory cytokines is an independent prognostic factor in patients with gastric cancer. Anticancer. Res. 2009, 29, 5005–5012. [Google Scholar]
- Wang, J.; Liu, J.; Chang, Q.; Yang, B.; Li, S.; Gu, C. The association between preoperative serum interleukin-6 levels and postoperative prognosis in patients with T2 gallbladder cancer. J. Surg. Oncol. 2018, 117, 1672–1678. [Google Scholar] [CrossRef]
- Kersten, C.; Louhimo, J.; Ålgars, A.; Lahdesmaki, A.; Cvancerova, M.; Stenstedt, K.; Haglund, C.; Gunnarsson, U. Increased C-reactive protein implies a poorer stage-specific prognosis in colon cancer. Acta Oncol. 2013, 52, 1691–1698. [Google Scholar] [CrossRef]
- McMillan, D.C. The systemic inflammation-based Glasgow Prognostic Score: A decade of experience in patients with cancer. Cancer Treat. Rev. 2013, 39, 534–540. [Google Scholar] [CrossRef] [PubMed]
- Plas, M.; Rotteveel, E.; Izaks, G.; Spikman, J.; van der Wal-Huisman, H.; van Etten, B.; Absalom, A.; Mourits, M.; de Bock, G.; van Leeuwen, B. Cognitive decline after major oncological surgery in the elderly. Eur. J. Cancer 2017, 86, 394–402. [Google Scholar] [CrossRef] [PubMed]
- Weerink, L.B.M.; Van Leeuwen, B.L.; Msc, S.A.M.G.; Absalom, A.R.; Huisman, M.G.; Msc, H.V.D.W.-H.; Izaks, G.J.; De Bock, G.H. Vitamin Status and the Development of Postoperative Cognitive Decline in Elderly Surgical Oncologic Patients. Ann. Surg. Oncol. 2018, 25, 231–238. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Du Msc, J.; Plas, M.; Absalom, A.R.; Leeuwen, B.L.; De Bock, G.H. The association of preoperative anxiety and depression with neurocognitive disorder following oncological surgery. J. Surg. Oncol. 2020, 121, 676–687. [Google Scholar] [CrossRef] [Green Version]
- Bras, L.; Driessen, D.A.J.J.; De Vries, J.; Festen, S.; Van Der Laan, B.F.A.M.; Van Leeuwen, B.L.; De Bock, G.H.; Halmos, G.B. Patients with head and neck cancer: Are they frailer than patients with other solid malignancies? Eur. J. Cancer Care 2019, 29, e13170. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Amdur, R.L.; Feldman, H.I.; Gupta, J.; Yang, W.; Kanetsky, P.; Shlipak, M.; Rahman, M.; Lash, J.P.; Townsend, R.R.; Ojo, A.; et al. Inflammation and Progression of CKD: The CRIC Study. Clin. J. Am. Soc. Nephrol. 2016, 11, 1546–1556. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Panichi, V.; Maggiore, U.; Taccola, D.; Migliori, M.; Rizza, G.M.; Consani, C.; Bertini, A.; Sposini, S.; Perez-Garcia, R.; Rindi, P.; et al. Interleukin-6 is a stronger predictor of total and cardiovascular mortality than C-reactive protein in haemodialysis patients. Nephrol. Dial. Transplant. 2004, 19, 1154–1160. [Google Scholar] [CrossRef] [Green Version]
- Clyne, B.; Olshaker, J.S. The C-reactive protein. J. Emerg. Med. 1999, 17, 1019–1025. [Google Scholar] [CrossRef]
- Morley, J.J.; Kushner, I. SERUM C-REACTIVE PROTEIN LEVELS IN DISEASE. Ann. N. Y. Acad. Sci. 1982, 389, 406–418. [Google Scholar] [CrossRef]
- Hrab, M.; Olek-Hrab, K.; Antczak, A.; Kwias, Z.; Milecki, T. Interleukin-6 (IL-6) and C-reactive protein (CRP) concentration prior to total nephrectomy are prognostic factors in localized renal cell carcinoma (RCC). Rep. Pr. Oncol. Radiother. 2013, 18, 304–309. [Google Scholar] [CrossRef] [Green Version]
- Lopez-Pastorini, A.; Riedel, R.; Koryllos, A.; Beckers, F.; Ludwig, C.; Stoelben, E. The impact of preoperative elevated serum C-reactive protein on postoperative morbidity and mortality after anatomic resection for lung cancer. Lung Cancer 2017, 109, 68–73. [Google Scholar] [CrossRef]
- Ventura, M.T.; Casciaro, M.; Gangemi, S.; Buquicchio, R. Immunosenescence in aging: Between immune cells depletion and cytokines up-regulation. Clin. Mol. Allergy 2017, 15, 1–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- De Martinis, M.; Franceschi, C.; Monti, D.; Ginaldi, L. Inflamm-ageing and lifelong antigenic load as major determinants of ageing rate and longevity. FEBS Lett. 2005, 579, 2035–2039. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Suzuki, K. Chronic Inflammation as an Immunological Abnormality and Effectiveness of Exercise. Biomolecules 2019, 9, 223. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Raposo, T.; Beirão, B.; Pang, L.; Queiroga, F.; Argyle, D. Inflammation and cancer: Till death tears them apart. Vet. J. 2015, 205, 161–174. [Google Scholar] [CrossRef] [PubMed]
- De Martinis, M.; Franceschi, C.; Monti, D.; Ginaldi, L. Inflammation markers predicting frailty and mortality in the elderly. Exp. Mol. Pathol. 2006, 80, 219–227. [Google Scholar] [CrossRef] [PubMed]
- Franceschi, C.; Capri, M.; Monti, D.; Giunta, S.; Olivieri, F.; Sevini, F.; Panourgia, M.P.; Invidia, L.; Celani, L.; Scurti, M.; et al. Inflammaging and anti-inflammaging: A systemic perspective on aging and longevity emerged from studies in humans. Mech. Ageing Dev. 2007, 128, 92–105. [Google Scholar] [CrossRef]
- Minciullo, P.L.; Catalano, A.; Mandraffino, G.; Casciaro, M.; Crucitti, A.; Maltese, G.; Morabito, N.; Lasco, A.; Gangemi, S.; Basile, G. Inflammaging and Anti-Inflammaging: The Role of Cytokines in Extreme Longevity. Arch. Immunol. Ther. Exp. 2016, 64, 111–126. [Google Scholar] [CrossRef]
- Stanilov, N.; Miteva, L.; Jovchev, J.; Cirovski, G.; Stanilova, S. The prognostic value of preoperative serum levels of IL-12p40 and IL-23 for survival of patients with colorectal cancer. APMIS 2014, 122, 1223–1229. [Google Scholar] [CrossRef]
- Maeda, Y.; Takeuchi, H.; Matsuda, S.; Okamura, A.; Fukuda, K.; Miyasho, T.; Nakamura, R.; Suda, K.; Wada, N.; Kawakubo, H.; et al. Clinical significance of preoperative serum concentrations of interleukin-6 as a prognostic marker in patients with esophageal cancer. Esophagus 2019, 17, 279–288. [Google Scholar] [CrossRef] [PubMed]
- Cesari, M.; Kritchevsky, S.B.; Nicklas, B.; Kanaya, A.M.; Patrignani, P.; Tacconelli, S.; Tranah, G.J.; Tognoni, G.; Harris, T.B.; Incalzi, R.A.; et al. Oxidative Damage, Platelet Activation, and Inflammation to Predict Mobility Disability and Mortality in Older Persons: Results From the Health Aging and Body Composition Study. J. Gerontol. Ser. A Boil. Sci. Med. Sci. 2012, 67, 671–676. [Google Scholar] [CrossRef] [PubMed]
- Sproston, N.R.; Ashworth, J.J. Role of C-Reactive Protein at Sites of Inflammation and Infection. Front. Immunol. 2018, 9, 754. [Google Scholar] [CrossRef] [PubMed]
- Takata, S.; Wada, H.; Tamura, M.; Koide, T.; Higaki, M.; Mikura, S.-I.; Yasutake, T.; Hirao, S.; Nakamura, M.; Honda, K.; et al. Kinetics of c-reactive protein (CRP) and serum amyloid A protein (SAA) in patients with community-acquired pneumonia (CAP), as presented with biologic half-life times. Biomarkers 2011, 16, 530–535. [Google Scholar] [CrossRef] [PubMed]
- Kuribayashi, T. Elimination half-lives of interleukin-6 and cytokine-induced neutrophil chemoattractant-1 synthesized in response to inflammatory stimulation in rats. Lab. Anim. Res. 2018, 34, 80–83. [Google Scholar] [CrossRef]
- Flick, D.A.; E Gifford, G.; Glfford, G.E. Pharmacokinetics of Murine Tumor Necrosis Factor. Immunopharmacol. Immunotoxicol. 1986, 8, 89–97. [Google Scholar] [CrossRef]
- Fagard, K.; Leonard, S.; Deschodt, M.; Devriendt, E.; Wolthuis, A.; Prenen, H.; Flamaing, J.; Milisen, K.; Wildiers, H.; Kenis, C. The impact of frailty on postoperative outcomes in individuals aged 65 and over undergoing elective surgery for colorectal cancer: A systematic review. J. Geriatr. Oncol. 2016, 7, 479–491. [Google Scholar] [CrossRef]
- Bouillon, K.; Kivimaki, M.; Hamer, M.; Sabia, S.; I Fransson, E.; Singh-Manoux, A.; Gale, C.R.; Batty, G.D. Measures of frailty in population-based studies: An overview. BMC Geriatr. 2013, 13, 64. [Google Scholar] [CrossRef] [Green Version]
- Mody, L.; Miller, D.K.; McGloin, J.M.; Freeman, M.; Marcantonio, E.R.; Magaziner, J.; Studenski, S. Recruitment and Retention of Older Adults in Aging Research. J. Am. Geriatr. Soc. 2008, 56, 2340–2348. [Google Scholar] [CrossRef]
Patient and Surgical Characteristics | Overall (n = 328) | Alive >3 Years after Surgery (n = 209) | Deceased ≤3 Years after Surgery (n = 119) |
---|---|---|---|
Age, mean (SEM), y | 72.7 (0.3) | 72.4 (0.4) | 73.3 (0.5) |
Gender, No. (%) | |||
Female | 150 (46) | 97 (65) | 53 (35) |
Male | 178 (54) | 112 (63) | 66 (37) |
BMI a, No. (%) | - | - | - |
<30 kg/m2 | 262 (80) | 167 (64) | 95 (36) |
≥30 kg/m2 | 66 (20) | 42 (64) | 24 (36) |
Charlson comorbidity index (CCI), mean (SEM) * | 4 (0.1) | 4 (0.1) | 4 (0.2) |
Groningen Frailty Indicator (GFI), mean (SEM) | 2 (0.1) | 2 (0.1) | 3 (0.2) |
Tumor Location, No. (%) | |||
Colorectal | 101 (31) | 68 (67) | 33 (33) |
Gastroesophageal | 44 (13) | 24 (55) | 20 (45) |
Gynecological | 54 (16) | 37 (69) | 17 (31) |
Skin | 42 (13) | 28 (67) | 14 (33) |
Soft tissue | 39 (12) | 26 (67) | 13 (33) |
Other | 48 (15) | 26 (54) | 22 (46) |
Tumor type, No. (%) | |||
Carcinoma | 233 (71) | 144 (62) | 89 (38) |
Sarcoma | 34 (10) | 24 (71) | 10 (29) |
Melanoma | 35 (11) | 24 (69) | 11 (31) |
Other malignancy | 26 (8) | 17 (65) | 9 (35) |
Disease stage, No. (%) | |||
I | 79 (24) | 64 (81) | 15 (19) |
II | 85 (26) | 62 (73) | 23 (27) |
III | 89 (27) | 49 (55) | 40 (45) |
IV | 75 (23) | 34 (45) | 41 (55) |
Neo-adjuvant treatment, No. (%) | |||
None | 233 (71) | 152 (65) | 81 (35) |
Chemotherapy | 30 (9) | 16 (53) | 14 (47) |
Radiation | 20 (6) | 16 (80) | 4 (20) |
Combination | 45 (14) | 25 (56) | 20 (44) |
Biomarkers T0, mean (SEM) | |||
CRP b (mg/L) | 12.7 (1.2) | 11.4 (1.6) | 14.9 (2.0) |
IL c-1β (pg/mL) | 14.5 (5.4) | 14.0 (7.2) | 15.4 (7.9) |
IL-6 (pg/mL) | 27.6 (8.5) | 34.7 (13.1) | 15.2 (4.4) |
IL-10 (pg/ mL) | 29.0 (7.1) | 32.8 (10.8) | 22.2 (5.2) |
IL-12 (pg/mL) | 13.1 (6.8) | 18.5 (10.6) | 3.8 (2.3) |
TNF d-α (pg/mL) | 46.1 (17.3) | 54.8 (26.2) | 30.8 (11.8) |
Type of surgery, No. (%) | |||
Intracavitary (thorax/abdomen) | 229 (70) | 136 (59) | 93 (41) |
Extremities/superficial | 99 (30) | 73 (74) | 26 (26) |
Type of anesthesia, No. (%) | |||
Regional | 10 (3) | 8 (80) | 2 (20) |
General | 153 (47) | 99 (65) | 54 (35) |
Regional + general | 165 (50) | 102 (62) | 63 (38) |
Duration of anesthesia in minutes, mean (SEM) | 262 (9) | 250 (11) | 283 (18) |
Postoperative complications, No. (%) | |||
Clavien Dindo ≥3 | 45 (14) | 21 (47) | 24 (53) |
Clavien Dindo <3 | 283 (86) | 188 (66) | 95 (34) |
Covariates | Univariate Model HR a (95% CI) b | Multivariate Model (Overall) HR a (95% CI) b | |
---|---|---|---|
Biomarkers c T0 | |||
CRP | <10 mg/L | Ref. | Ref. |
- | ≥10 mg/L | 1.58 (1.10–2.28) * | 1.50 (1.04–2.16) * |
IL-1β | <0.9 pg/mL | Ref. | - |
- | ≥0.9 pg/mL | 1.10 (0.73–1.65) | - |
IL-6 | <4.2 pg/mL | Ref. | - |
- | ≥4.2 pg/mL | 1.48 (1.00–2.18) * | - |
IL-10 | <19.8 pg/mL | Ref. | - |
- | ≥19.8 pg/mL | 1.16 (0.78–1.73) | - |
IL-12 | <1.2 pg/mL | Ref. | - |
- | ≥1.2 pg/mL | 1.17 (0.79–1.75) | - |
TNF-α | <0.9 pg/mL | Ref. | - |
- | ≥0.9 pg/mL | 0.93 (0.61–1.42) | - |
Age (years) | 1.02 (0.99–1.05) | - | |
Gender | |||
Female | Ref. | - | |
Male | 1.11 (0.77–1.59) | - | |
CCI | |||
Low (<3) | Ref. | - | |
High (≥3) | 1.44 (0.99–2.08) | - | |
GFI | |||
Low (<4) | Ref. | - | |
High (≥4) | 1.50 (0.99–2.26) | - | |
Tumor Type | |||
Carcinoma | 1.28 (0.85–1.94) | - | |
Other malignancy | Ref. | - | |
Disease Stage | |||
I | Ref. *** | Ref. *** | |
II | 1.51 (0.79–2.90) | 1.50 (0.78–2.88) | |
III | 2.77 (1.53–5.02) | 2.63 (1.45–4.77) | |
IV | 3.77 (2.08–6.81) | 3.79 (2.10–6.85) | |
Neo-adjuvant Treatment | |||
None | Ref. | - | |
Radiation | 1.44 (0.82–2.53) | - | |
Chemotherapy | 0.54 (0.20–1.46) | - | |
Combination | 1.42 (0.87–2.32) | - | |
Type of surgery | |||
Intra-abdominal/thoracic | 1.69 (1.10–2.61) ** | - | |
Extremities/superficial | Ref. | - | |
Type of anesthesia | |||
Regional | Ref. | - | |
General | 1.99 (0.48–8.15) | - | |
Regional + general | 2.30 (0.56–9.40) | - | |
Duration anesthesia (min) | |||
≤180 min | Ref. | - | |
>180 min | 1.04 (0.72–1.50) | - | |
Postoperative complications | |||
Clavien Dindo < 3 | Ref. | Ref. | |
Clavien Dindo ≥ 3 | 1.96 (1.25–3.06) ** | 1.81 (1.15–2.84) * |
Covariates | Univariate Model HR a (95% CI) b | Multivariate Model (Overall) HR a (95% CI) b | |
---|---|---|---|
Biomarkers c T0 | - | - | |
CRP | <10 mg/L | Ref. | Ref. |
- | ≥10 mg/L | 2.01 (1.01–3.98) * | 2.40 (1.20–4.81) * |
IL-1β | <0.9 pg/mL | Ref. | - |
- | ≥0.9 pg/mL | 1.68 (0.81–3.46) | - |
IL-6 | <4.2 pg/mL | Ref. | - |
- | ≥4.2 pg/mL | 2.05 (1.02–4.13) * | - |
IL-10 | <19.8 pg/mL | Ref. | - |
- | ≥19.8 pg/mL | 0.90 (0.42–1.94) | - |
IL-12 | <1.2 pg/mL | Ref. | - |
- | ≥1.2 pg/mL | 2.21 (1.11–4.39) * | - |
TNF-α | <0.9 pg/mL | Ref. | - |
- | ≥0.9 pg/mL | 1.54 (0.76–3.14) | - |
Age (years) | 1.01 (0.95–1.08) | - | |
Gender | |||
Female | Ref. | - | |
Male | 1.12 (0.54–2.36) | - | |
CCI | |||
Low (<3) | Ref. | - | |
High (≥3) | 1.60 (0.74–3.45) | - | |
GFI | |||
Low (<4) | Ref. | - | |
High (≥4) | 0.37 (0.09–1.53) | - | |
Disease Stage | |||
I + II | Ref. | Ref. | |
III + IV | 3.05 (1.50–6.21) ** | 3.94 (1.89–8.22) *** | |
Neo-adjuvant Treatment | |||
None | Ref. | - | |
Chemotherapy or radiation | 0.95 (0.36–2.53) | - | |
Combination | 1.18 (0.52–2.67) | - | |
Duration anesthesia (min) | |||
≤180 min | Ref. | - | |
>180 min | 0.54 (0.27–1.10) | - | |
Postoperative complications | |||
Clavien Dindo <3 | Ref. | Ref. | |
Clavien Dindo ≥3 | 2.83 (1.34–5.97) ** | 3.54 (1.64–7.64) ** |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Brattinga, B.; Rutgers, A.; De Haan, J.J.; Absalom, A.R.; van der Wal-Huisman, H.; de Bock, G.H.; van Leeuwen, B.L. Preoperative Inflammatory Markers as a Predictor of Three-Year Overall Survival in Older Cancer Patients Undergoing Oncologic Surgery. Cancers 2021, 13, 1824. https://doi.org/10.3390/cancers13081824
Brattinga B, Rutgers A, De Haan JJ, Absalom AR, van der Wal-Huisman H, de Bock GH, van Leeuwen BL. Preoperative Inflammatory Markers as a Predictor of Three-Year Overall Survival in Older Cancer Patients Undergoing Oncologic Surgery. Cancers. 2021; 13(8):1824. https://doi.org/10.3390/cancers13081824
Chicago/Turabian StyleBrattinga, Baukje, Abraham Rutgers, Jacco J. De Haan, Anthony R. Absalom, Hanneke van der Wal-Huisman, Geertruida H. de Bock, and Barbara L. van Leeuwen. 2021. "Preoperative Inflammatory Markers as a Predictor of Three-Year Overall Survival in Older Cancer Patients Undergoing Oncologic Surgery" Cancers 13, no. 8: 1824. https://doi.org/10.3390/cancers13081824
APA StyleBrattinga, B., Rutgers, A., De Haan, J. J., Absalom, A. R., van der Wal-Huisman, H., de Bock, G. H., & van Leeuwen, B. L. (2021). Preoperative Inflammatory Markers as a Predictor of Three-Year Overall Survival in Older Cancer Patients Undergoing Oncologic Surgery. Cancers, 13(8), 1824. https://doi.org/10.3390/cancers13081824