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      Controlling Nutritional Status (CONUT) as a Novel Postoperative Prognostic Marker in Breast Cancer Patients: A Retrospective Study

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          Abstract

          Purpose

          This investigation seeks to elucidate the potential prognostic significance as well as the clinical utility of the controlling nutritional status (CONUT) score in breast cancer patients.

          Methods

          Breast cancer patients managed in our center between January 2010 and December 2016 were recruited for our study. They comprised 187 patients who did not undergo neoadjuvant chemotherapy and 194 who did. A receiver operating characteristic curve (ROC) was utilized in identifying the ideal cut-off CONUT value. This cut-off score was then used to reclassify patients into those with high CONUT scores (≥1) and low CONUT scores (<1). The outcomes were analyzed by statistical methods.

          Results

          Univariate and multivariate Cox regression survival analyses revealed that a CONUT score cut-off of 1 was able to significantly predict duration of disease-free survival (DFS) ( p < 0.001; hazard ratio [HR]: 3.184; 95% CI: 1.786-5.677; and p < 0.001; HR: 2.465; 95% CI: 1.642-3.700) and overall survival (OS) ( p < 0.001; HR: 2.326; 95% CI: 1.578-3.429; and p < 0.001; HR: 2.775; 95% CI: 1.791-4.300). The mean DFS and OS in those with lower CONUT scores were 41.59 (95% CI: 37.66-45.51 months) and 77.34 months (95% CI: 71.79-82.90 months), respectively. On the other hand, the average DFS and OS for all individuals in the raised CONUT score group were 39.18 (95% CI: 34.41-43.95 months) and 71.30 months (95% CI: 65.47-77.12 months), respectively. Moreover, Kaplan-Meier survival analysis revealed that those in the raised CONUT score cohort had remarkably worse DFS and OS survival rates compared to individuals in the low CONUT score cohort (Log-rank test, DFS: χ 2 = 12.900, p = 0.0003, and OS: χ 2 = 16.270, p < 0.0001).

          Conclusion

          The survival times of breast cancer patients may be reliably predicted using the CONUT score. This score is an easy, convenient, readily accessible, and clinically significant means of prognosticating patients with breast cancer.

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          Ahmedin Jemal, Lindsey A Torre, Rebecca Siegel … (2018)
          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Cancer statistics, 2020

            Rebecca Siegel, Kimberly D Miller, Ahmedin Jemal (2020)
            Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths that will occur in the United States and compiles the most recent data on population-based cancer occurrence. Incidence data (through 2016) were collected by the Surveillance, Epidemiology, and End Results Program; the National Program of Cancer Registries; and the North American Association of Central Cancer Registries. Mortality data (through 2017) were collected by the National Center for Health Statistics. In 2020, 1,806,590 new cancer cases and 606,520 cancer deaths are projected to occur in the United States. The cancer death rate rose until 1991, then fell continuously through 2017, resulting in an overall decline of 29% that translates into an estimated 2.9 million fewer cancer deaths than would have occurred if peak rates had persisted. This progress is driven by long-term declines in death rates for the 4 leading cancers (lung, colorectal, breast, prostate); however, over the past decade (2008-2017), reductions slowed for female breast and colorectal cancers, and halted for prostate cancer. In contrast, declines accelerated for lung cancer, from 3% annually during 2008 through 2013 to 5% during 2013 through 2017 in men and from 2% to almost 4% in women, spurring the largest ever single-year drop in overall cancer mortality of 2.2% from 2016 to 2017. Yet lung cancer still caused more deaths in 2017 than breast, prostate, colorectal, and brain cancers combined. Recent mortality declines were also dramatic for melanoma of the skin in the wake of US Food and Drug Administration approval of new therapies for metastatic disease, escalating to 7% annually during 2013 through 2017 from 1% during 2006 through 2010 in men and women aged 50 to 64 years and from 2% to 3% in those aged 20 to 49 years; annual declines of 5% to 6% in individuals aged 65 years and older are particularly striking because rates in this age group were increasing prior to 2013. It is also notable that long-term rapid increases in liver cancer mortality have attenuated in women and stabilized in men. In summary, slowing momentum for some cancers amenable to early detection is juxtaposed with notable gains for other common cancers.
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              New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

              E A Eisenhauer, P Therasse, J. Bogaerts … (2009)
              Assessment of the change in tumour burden is an important feature of the clinical evaluation of cancer therapeutics: both tumour shrinkage (objective response) and disease progression are useful endpoints in clinical trials. Since RECIST was published in 2000, many investigators, cooperative groups, industry and government authorities have adopted these criteria in the assessment of treatment outcomes. However, a number of questions and issues have arisen which have led to the development of a revised RECIST guideline (version 1.1). Evidence for changes, summarised in separate papers in this special issue, has come from assessment of a large data warehouse (>6500 patients), simulation studies and literature reviews. HIGHLIGHTS OF REVISED RECIST 1.1: Major changes include: Number of lesions to be assessed: based on evidence from numerous trial databases merged into a data warehouse for analysis purposes, the number of lesions required to assess tumour burden for response determination has been reduced from a maximum of 10 to a maximum of five total (and from five to two per organ, maximum). Assessment of pathological lymph nodes is now incorporated: nodes with a short axis of 15 mm are considered measurable and assessable as target lesions. The short axis measurement should be included in the sum of lesions in calculation of tumour response. Nodes that shrink to <10mm short axis are considered normal. Confirmation of response is required for trials with response primary endpoint but is no longer required in randomised studies since the control arm serves as appropriate means of interpretation of data. Disease progression is clarified in several aspects: in addition to the previous definition of progression in target disease of 20% increase in sum, a 5mm absolute increase is now required as well to guard against over calling PD when the total sum is very small. Furthermore, there is guidance offered on what constitutes 'unequivocal progression' of non-measurable/non-target disease, a source of confusion in the original RECIST guideline. Finally, a section on detection of new lesions, including the interpretation of FDG-PET scan assessment is included. Imaging guidance: the revised RECIST includes a new imaging appendix with updated recommendations on the optimal anatomical assessment of lesions. A key question considered by the RECIST Working Group in developing RECIST 1.1 was whether it was appropriate to move from anatomic unidimensional assessment of tumour burden to either volumetric anatomical assessment or to functional assessment with PET or MRI. It was concluded that, at present, there is not sufficient standardisation or evidence to abandon anatomical assessment of tumour burden. The only exception to this is in the use of FDG-PET imaging as an adjunct to determination of progression. As is detailed in the final paper in this special issue, the use of these promising newer approaches requires appropriate clinical validation studies.
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                Author and article information

                Contributors
                Yi Fang:
                ORCID: https://orcid.org/0000-0002-2657-0146
                Jing Wang:
                ORCID: https://orcid.org/0000-0002-3224-3993
                Journal
                Journal ID (nlm-ta): Biomed Res Int
                Journal ID (iso-abbrev): Biomed Res Int
                Journal ID (publisher-id): BMRI
                Title: BioMed Research International
                Publisher: Hindawi
                ISSN (Print): 2314-6133
                ISSN (Electronic): 2314-6141
                Publication date Collection: 2022
                Publication date (Electronic): 9 December 2022
                Volume: 2022
                Electronic Location Identifier: 3254581
                Affiliations
                1Department of Breast Surgical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
                2Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
                Author notes

                Academic Editor: Krzysztof Siemianowicz

                Author information
                https://orcid.org/0000-0003-4690-8447
                https://orcid.org/0000-0002-2657-0146
                https://orcid.org/0000-0002-3224-3993
                Article
                DOI: 10.1155/2022/3254581
                PMC ID: 9757942
                PubMed ID: 36531650
                SO-VID: a7fa88e8-942a-4ac0-8c5c-866c31336551
                Copyright © Copyright © 2022 Mengliu Zhu et al.
                License:

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 7 October 2022
                Date revision received : 9 November 2022
                Date accepted : 12 November 2022
                Funding
                Funded by: Clinical Research Physician Program of Tongji Medical College, HUST
                Award ID: 5001540018
                Funded by: Wuhan Youth Cadre Project
                Award ID: 2017zqnlxr02
                Award ID: 2017zqnlxr01
                Funded by: National Basic Research Program of China (973 Program)
                Award ID: 2018YFC1312100
                Funded by: Peking Union Medical College Youth Research Funds
                Award ID: 3332015157
                Funded by: Capital Public Health Education, Beijing Science and Technology Program
                Award ID: Z171100000417028
                Funded by: National Natural Science Foundation of China
                Award ID: 81802676
                Award ID: 81872160
                Categories
                Subject: Research Article

                Data availability:

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