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      Distinguishing optimal candidates for primary tumor resection in patients with metastatic lung adenocarcinoma: A predictive model based on propensity score matching

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          Abstract

          Background

          Primary tumor resection is associated with survival benefits in patients with metastatic lung adenocarcinoma (mLUAD). However, there are no established methods to determine which individuals would benefit from surgery. Therefore, we developed a model to predict the patients who are likely to benefit from surgery in terms of survival.

          Methods

          Data on patients with mLUAD were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Depending on whether surgery was performed on the primary tumor, patients were categorized into two groups: cancer-directed surgery (CDS) and no-cancer-directed surgery (No-CDS). Propensity Score Matching (PSM) was utilized to address bias between the CDS and No-CDS groups. The prognostic impact of CDS was assessed using Kaplan-Meier analysis and Cox proportional hazard models. Subsequently, we constructed a nomogram to predict the potential for surgical benefits based on multivariable logistic regression analysis using preoperative factors.

          Results

          A total of 89,039 eligible patients were identified, including 6.4% (5705) who underwent surgery. Following PSM, the CDS group demonstrated a significantly longer median overall survival (mOS) compared with the No-CDS group (23 [21–25] vs. 7 [7–8] months; P < 0.001). The nomogram showed robust performance in both the training and validation sets (area under the curve [AUC]: 0.698 and 0.717, respectively), and the calibration curves exhibited high consistency. The nomogram proved clinically valuable according to decision curve analysis (DCA). According to this nomogram, surgical patients were categorized into two groups: no-benefit candidates and benefit candidates groups. Compared with the no-benefit candidate group, the benefit candidate group was associated with longer survival (mOS: 25 vs. 6 months, P < 0.001). Furthermore, no difference in survival was observed between the no-benefit candidates and the no-surgery groups (mOS: 6 vs. 7 months, P = 0.9).

          Conclusions

          A practical nomogram was developed to identify optimal CDS candidates among patients with mLUAD.

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          Most cited references45

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Cancer statistics, 2022

            Each year, the American Cancer Society estimates the numbers of new cancer cases and deaths in the United States and compiles the most recent data on population-based cancer occurrence and outcomes. Incidence data (through 2018) 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 2019) were collected by the National Center for Health Statistics. In 2022, 1,918,030 new cancer cases and 609,360 cancer deaths are projected to occur in the United States, including approximately 350 deaths per day from lung cancer, the leading cause of cancer death. Incidence during 2014 through 2018 continued a slow increase for female breast cancer (by 0.5% annually) and remained stable for prostate cancer, despite a 4% to 6% annual increase for advanced disease since 2011. Consequently, the proportion of prostate cancer diagnosed at a distant stage increased from 3.9% to 8.2% over the past decade. In contrast, lung cancer incidence continued to decline steeply for advanced disease while rates for localized-stage increased suddenly by 4.5% annually, contributing to gains both in the proportion of localized-stage diagnoses (from 17% in 2004 to 28% in 2018) and 3-year relative survival (from 21% to 31%). Mortality patterns reflect incidence trends, with declines accelerating for lung cancer, slowing for breast cancer, and stabilizing for prostate cancer. In summary, progress has stagnated for breast and prostate cancers but strengthened for lung cancer, coinciding with changes in medical practice related to cancer screening and/or treatment. More targeted cancer control interventions and investment in improved early detection and treatment would facilitate reductions in cancer mortality.
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              Nomograms in oncology: more than meets the eye.

              Nomograms are widely used as prognostic devices in oncology and medicine. With the ability to generate an individual probability of a clinical event by integrating diverse prognostic and determinant variables, nomograms meet our desire for biologically and clinically integrated models and fulfill our drive towards personalised medicine. Rapid computation through user-friendly digital interfaces, together with increased accuracy, and more easily understood prognoses compared with conventional staging, allow for seamless incorporation of nomogram-derived prognosis to aid clinical decision making. This has led to the appearance of many nomograms on the internet and in medical journals, and an increase in nomogram use by patients and physicians alike. However, the statistical foundations of nomogram construction, their precise interpretation, and evidence supporting their use are generally misunderstood. This issue is leading to an under-appreciation of the inherent uncertainties regarding nomogram use. We provide a systematic, practical approach to evaluating and comprehending nomogram-derived prognoses, with particular emphasis on clarifying common misconceptions and highlighting limitations.
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                26 March 2024
                15 April 2024
                26 March 2024
                : 10
                : 7
                : e27768
                Affiliations
                [1]Fourth Hospital of Hebei Medical University, Qiao Dong Qu, Shi Jia Zhuang Shi, He Bei Sheng, 050010, China
                Author notes
                [* ]Corresponding author. Department of Immuno-Oncology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050011, China. drwangzhiyu@ 123456hebmu.edu.cn
                Article
                S2405-8440(24)03799-X e27768
                10.1016/j.heliyon.2024.e27768
                11059407
                38690000
                27da0751-917c-43e2-a9fb-7f9082514b1b
                © 2024 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 8 June 2023
                : 4 March 2024
                : 6 March 2024
                Categories
                Research Article

                metastatic lung adenocarcinoma (mluad),surgery,seer,prognosis factor,risk factor,nomogram

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