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      Analysis of Delayed Surgical Treatment and Oncologic Outcomes in Clinical Stage I Non–Small Cell Lung Cancer

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          Abstract

          This cohort study examines the association between delayed surgical treatment and recurrence and survival among patients with non–small cell lung cancer in a cohort of patients treated in the Veterans Health Administration system.

          Key Points

          Question

          What is the association between delayed surgical treatment and oncologic outcomes among patients with non–small cell lung cancer (NSCLC)?

          Findings

          In this retrospective cohort study of 9904 patients with clinical stage I NSCLC using data from the Veterans Health Administration, surgical procedures that were delayed more than 12 weeks from the date of radiographic diagnosis were associated with increased risk of recurrence and worse overall survival.

          Meaning

          These findings suggest that patients with clinical stage I NSCLC should receive surgical treatment within at least 12 weeks of radiographic diagnosis.

          Abstract

          Importance

          The association between delayed surgical treatment and oncologic outcomes in patients with non–small cell lung cancer (NSCLC) is poorly understood given that prior studies have used imprecise definitions for the date of cancer diagnosis.

          Objective

          To use a uniform method to quantify surgical treatment delay and to examine its association with several oncologic outcomes.

          Design, Setting, and Participants

          This retrospective cohort study was conducted using a novel data set from the Veterans Health Administration (VHA) system. Included patients had clinical stage I NSCLC and were undergoing resection from 2006 to 2016 within the VHA system. Time to surgical treatment (TTS) was defined as the time between preoperative diagnostic computed tomography imaging and surgical treatment. We evaluated the association between TTS and several delay-associated outcomes using restricted cubic spline functions. Data analyses were performed in November 2021.

          Exposure

          Wait time between cancer diagnosis and surgical treatment (ie, TTS).

          Main Outcomes and Measures

          Several delay-associated oncologic outcomes, including pathologic upstaging, resection with positive margins, and recurrence, were assessed. We also assessed overall survival.

          Results

          Among 9904 patients who underwent surgical treatment for clinical stage I NSCLC, 9539 (96.3%) were men, 4972 individuals (50.5%) were currently smoking, and the mean (SD) age was 67.7 (7.9) years. The mean (SD) TTS was 70.1 (38.6) days. TTS was not associated with increased risk of pathologic upstaging or positive margins. Recurrence was detected in 4158 patients (42.0%) with median (interquartile range) follow-up of 6.15 (2.51-11.51) years. Factors associated with increased risk of recurrence included younger age (hazard ratio [HR] for every 1-year increase in age, 0.992; 95% CI, 0.987-0.997; P = .003), higher Charlson Comorbidity Index score (HR for every 1-unit increase in composite score, 1.055; 95% CI, 1.037-1.073; P < .001), segmentectomy (HR vs lobectomy, 1.352; 95% CI, 1.179-1.551; P < .001) or wedge resection (HR vs lobectomy, 1.282; 95% CI, 1.179-1.394; P < .001), larger tumor size (eg, 31-40 mm vs <10 mm; HR, 1.209; 95% CI, 1.051-1.390; P = .008), higher tumor grade (eg, II vs I; HR, 1.210; 95% CI, 1.085-1.349; P < .001), lower number of lymph nodes examined (eg, ≥10 vs <10; HR, 0.866; 95% CI, 0.803-0.933; P < .001), higher pathologic stage (III vs I; HR, 1.571; 95% CI, 1.351-1.837; P < .001), and longer TTS, with increasing risk after 12 weeks. For each week of surgical delay beyond 12 weeks, the hazard for recurrence increased by 0.4% (HR, 1.004; 95% CI, 1.001-1.006; P = .002). Factors associated with delayed surgical treatment included African American race (odds ratio [OR] vs White race, 1.267; 95% CI, 1.112-1.444; P < .001), higher area deprivation index [ADI] score (OR for every 1 unit increase in ADI score, 1.005; 95% CI, 1.002-1.007; P = .002), lower hospital case load (OR for every 1-unit increase in case load, 0.998; 95% CI, 0.998-0.999; P = .001), and year of diagnosis, with less recent procedures more likely to have delay (OR for each additional year, 0.900; 95% CI, 0.884-0.915; P < .001). Patients with surgical treatment within 12 weeks of diagnosis had significantly better overall survival than those with procedures delayed more than 12 weeks (HR, 1.132; 95% CI, 1.064-1.204; P < .001).

          Conclusions and Relevance

          Using a more precise definition for TTS, this study found that surgical procedures delayed more than 12 weeks were associated with increased risk of recurrence and worse survival. These findings suggest that patients with clinical stage I NSCLC should undergo expeditious treatment within that time frame.

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          Most cited references36

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          WHO Declares COVID-19 a Pandemic

          The World Health Organization (WHO) on March 11, 2020, has declared the novel coronavirus (COVID-19) outbreak a global pandemic (1). At a news briefing, WHO Director-General, Dr. Tedros Adhanom Ghebreyesus, noted that over the past 2 weeks, the number of cases outside China increased 13-fold and the number of countries with cases increased threefold. Further increases are expected. He said that the WHO is “deeply concerned both by the alarming levels of spread and severity and by the alarming levels of inaction,” and he called on countries to take action now to contain the virus. “We should double down,” he said. “We should be more aggressive.” Among the WHO’s current recommendations, people with mild respiratory symptoms should be encouraged to isolate themselves, and social distancing is emphasized and these recommendations apply even to countries with no reported cases (2). Separately, in JAMA, researchers report that SARS-CoV-2, the virus that causes COVID-19, was most often detected in respiratory samples from patients in China. However, live virus was also found in feces. They conclude: “Transmission of the virus by respiratory and extrarespiratory routes may help explain the rapid spread of disease.”(3). COVID-19 is a novel disease with an incompletely described clinical course, especially for children. In a recente report W. Liu et al described that the virus causing Covid-19 was detected early in the epidemic in 6 (1.6%) out of 366 children (≤16 years of age) hospitalized because of respiratory infections at Tongji Hospital, around Wuhan. All these six children had previously been completely healthy and their clinical characteristics at admission included high fever (>39°C) cough and vomiting (only in four). Four of the six patients had pneumonia, and only one required intensive care. All patients were treated with antiviral agents, antibiotic agents, and supportive therapies, and recovered after a median 7.5 days of hospitalization. (4). Risk factors for severe illness remain uncertain (although older age and comorbidity have emerged as likely important factors), the safety of supportive care strategies such as oxygen by high-flow nasal cannula and noninvasive ventilation are unclear, and the risk of mortality, even among critically ill patients, is uncertain. There are no proven effective specific treatment strategies, and the risk-benefit ratio for commonly used treatments such as corticosteroids is unclear (3,5). Septic shock and specific organ dysfunction such as acute kidney injury appear to occur in a significant proportion of patients with COVID-19–related critical illness and are associated with increasing mortality, with management recommendations following available evidence-based guidelines (3). Novel COVID-19 “can often present as a common cold-like illness,” wrote Roman Wöelfel et al. (6). They report data from a study concerning nine young- to middle-aged adults in Germany who developed COVID-19 after close contact with a known case. All had generally mild clinical courses; seven had upper respiratory tract disease, and two had limited involvement of the lower respiratory tract. Pharyngeal virus shedding was high during the first week of symptoms, peaking on day 4. Additionally, sputum viral shedding persisted after symptom resolution. The German researchers say the current case definition for COVID-19, which emphasizes lower respiratory tract disease, may need to be adjusted(6). But they considered only young and “normal” subjecta whereas the story is different in frail comorbid older patients, in whom COVID 19 may precipitate an insterstitial pneumonia, with severe respiratory failure and death (3). High level of attention should be paid to comorbidities in the treatment of COVID-19. In the literature, COVID-19 is characterised by the symptoms of viral pneumonia such as fever, fatigue, dry cough, and lymphopenia. Many of the older patients who become severely ill have evidence of underlying illness such as cardiovascular disease, liver disease, kidney disease, or malignant tumours. These patients often die of their original comorbidities. They die “with COVID”, but were extremely frail and we therefore need to accurately evaluate all original comorbidities. In addition to the risk of group transmission of an infectious disease, we should pay full attention to the treatment of the original comorbidities of the individual while treating pneumonia, especially in older patients with serious comorbid conditions and polipharmacy. Not only capable of causing pneumonia, COVID-19 may also cause damage to other organs such as the heart, the liver, and the kidneys, as well as to organ systems such as the blood and the immune system. Patients die of multiple organ failure, shock, acute respiratory distress syndrome, heart failure, arrhythmias, and renal failure (5,6). What we know about COVID 19? In December 2019, a cluster of severe pneumonia cases of unknown cause was reported in Wuhan, Hubei province, China. The initial cluster was epidemiologically linked to a seafood wholesale market in Wuhan, although many of the initial 41 cases were later reported to have no known exposure to the market (7). A novel strain of coronavirus belonging to the same family of viruses that cause severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS), as well as the 4 human coronaviruses associated with the common cold, was subsequently isolated from lower respiratory tract samples of 4 cases on 7 January 2020. On 30 January 2020, the WHO declared that the SARS-CoV-2 outbreak constituted a Public Health Emergency of International Concern, and more than 80, 000 confirmed cases had been reported worldwide as of 28 February 2020 (8). On 31 January 2020, the U.S. Centers for Disease Control and Prevention announced that all citizens returning from Hubei province, China, would be subject to mandatory quarantine for up to 14 days. But from China COVID 19 arrived to many other countries. Rothe C et al reported a case of a 33-year-old otherwise healthy German businessman :she became ill with a sore throat, chills, and myalgias on January 24, 2020 (9). The following day, a fever of 39.1°C developed, along with a productive cough. By the evening of the next day, he started feeling better and went back to work on January 27. Before the onset of symptoms, he had attended meetings with a Chinese business partner at his company near Munich on January 20 and 21. The business partner, a Shanghai resident, had visited Germany between January 19 and 22. During her stay, she had been well with no signs or symptoms of infection but had become ill on her flight back to China, where she tested positive for 2019-nCoV on January 26. This case of 2019-nCoV infection was diagnosed in Germany and transmitted outside Asia. However, it is notable that the infection appears to have been transmitted during the incubation period of the index patient, in whom the illness was brief and nonspecific. The fact that asymptomatic persons are potential sources of 2019-nCoV infection may warrant a reassessment of transmission dynamics of the current outbreak (9). Our current understanding of the incubation period for COVID-19 is limited. An early analysis based on 88 confirmed cases in Chinese provinces outside Wuhan, using data on known travel to and from Wuhan to estimate the exposure interval, indicated a mean incubation period of 6.4 days (95% CI, 5.6 to 7.7 days), with a range of 2.1 to 11.1 days. Another analysis based on 158 confirmed cases outside Wuhan estimated a median incubation period of 5.0 days (CI, 4.4 to 5.6 days), with a range of 2 to 14 days. These estimates are generally consistent with estimates from 10 confirmed cases in China (mean incubation period, 5.2 days [CI, 4.1 to 7.0 days] and from clinical reports of a familial cluster of COVID-19 in which symptom onset occurred 3 to 6 days after assumed exposure in Wuhan (10-12). The incubation period can inform several important public health activities for infectious diseases, including active monitoring, surveillance, control, and modeling. Active monitoring requires potentially exposed persons to contact local health authorities to report their health status every day. Understanding the length of active monitoring needed to limit the risk for missing infections is necessary for health departments to effectively use resources. A recent paper provides additional evidence for a median incubation period for COVID-19 of approximately 5 days (13). Lauer et al suggest that 101 out of every 10 000 cases will develop symptoms after 14 days of active monitoring or quarantinen (13). Whether this rate is acceptable depends on the expected risk for infection in the population being monitored and considered judgment about the cost of missing cases. Combining these judgments with the estimates presented here can help public health officials to set rational and evidence-based COVID-19 control policies. Note that the proportion of mild cases detected has increased as surveillance and monitoring systems have been strengthened. The incubation period for these severe cases may differ from that of less severe or subclinical infections and is not typically an applicable measure for those with asymptomatic infections In conclusion, in a very short period health care systems and society have been severely challenged by yet another emerging virus. Preventing transmission and slowing the rate of new infections are the primary goals; however, the concern of COVID-19 causing critical illness and death is at the core of public anxiety. The critical care community has enormous experience in treating severe acute respiratory infections every year, often from uncertain causes. The care of severely ill patients, in particular older persons with COVID-19 must be grounded in this evidence base and, in parallel, ensure that learning from each patient could be of great importance to care all population,
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            Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

            Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define Charlson and Elixhauser comorbidities in administrative data and assess the performance of the resulting algorithms. ICD-10 coding algorithms were developed by "translation" of the ICD-9-CM codes constituting Deyo's (for Charlson comorbidities) and Elixhauser's coding algorithms and by physicians' assessment of the face-validity of selected ICD-10 codes. The process of carefully developing ICD-10 algorithms also produced modified and enhanced ICD-9-CM coding algorithms for the Charlson and Elixhauser comorbidities. We then used data on in-patients aged 18 years and older in ICD-9-CM and ICD-10 administrative hospital discharge data from a Canadian health region to assess the comorbidity frequencies and mortality prediction achieved by the original ICD-9-CM algorithms, the enhanced ICD-9-CM algorithms, and the new ICD-10 coding algorithms. Among 56,585 patients in the ICD-9-CM data and 58,805 patients in the ICD-10 data, frequencies of the 17 Charlson comorbidities and the 30 Elixhauser comorbidities remained generally similar across algorithms. The new ICD-10 and enhanced ICD-9-CM coding algorithms either matched or outperformed the original Deyo and Elixhauser ICD-9-CM coding algorithms in predicting in-hospital mortality. The C-statistic was 0.842 for Deyo's ICD-9-CM coding algorithm, 0.860 for the ICD-10 coding algorithm, and 0.859 for the enhanced ICD-9-CM coding algorithm, 0.868 for the original Elixhauser ICD-9-CM coding algorithm, 0.870 for the ICD-10 coding algorithm and 0.878 for the enhanced ICD-9-CM coding algorithm. These newly developed ICD-10 and ICD-9-CM comorbidity coding algorithms produce similar estimates of comorbidity prevalence in administrative data, and may outperform existing ICD-9-CM coding algorithms.
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              The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classification for Lung Cancer.

              The IASLC Staging and Prognostic Factors Committee has collected a new database of 94,708 cases donated from 35 sources in 16 countries around the globe. This has now been analysed by our statistical partners at Cancer Research And Biostatistics and, in close collaboration with the members of the committee proposals have been developed for the T, N, and M categories of the 8th edition of the TNM Classification for lung cancer due to be published late 2016. In this publication we describe the methods used to evaluate the resultant Stage groupings and the proposals put forward for the 8th edition.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                27 May 2021
                May 2021
                27 May 2021
                : 4
                : 5
                : e2111613
                Affiliations
                [1 ]Division of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine in St Louis, Missouri
                [2 ]VA St Louis Health Care System, St Louis, Missouri
                [3 ]Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine in St Louis, Missouri
                Author notes
                Article Information
                Accepted for Publication: April 1, 2021.
                Published: May 27, 2021. doi:10.1001/jamanetworkopen.2021.11613
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Heiden BT et al. JAMA Network Open.
                Corresponding Author: Brendan T. Heiden, MD, Division of Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine in, St Louis, 660 S Euclid Ave, Campus Box 8234, St Louis, MO 63110 ( bheiden@ 123456wustl.edu ).
                Author Contributions: Mr Eaton and Dr Puri had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Heiden, Chang, Kreisel, Nava, Meyers, Kozower, Puri.
                Acquisition, analysis, or interpretation of data: Heiden, Eaton, Engelhardt, Chang, Yan, Patel, Meyers.
                Drafting of the manuscript: Heiden, Eaton.
                Critical revision of the manuscript for important intellectual content: All authors.
                Statistical analysis: Heiden, Eaton, Yan, Kozower.
                Obtained funding: Puri.
                Administrative, technical, or material support: Heiden, Engelhardt, Chang, Patel.
                Supervision: Heiden, Chang, Kreisel, Meyers, Puri.
                Conflict of Interest Disclosures: Dr Chang reported receiving grants from the US Department of Veteran Affairs (VA) during the conduct of the study. Dr Kreisel reported receiving personal fees from Compass Therapeutics outside the submitted work and having a patent pending entitled “Compositions and methods for detecting CCR2 receptors.” Dr Puri reported receiving consulting fees from PrecisCa outside the submitted work and ownership of stock in Intuitive Surgical by his spouse. No other disclosures were reported.
                Funding/Support: Dr Heiden was supported by grant No. 5T32HL007776-25 from the National Institutes of Health. Drs Puri, Chang, and Yan were supported by grant No. 1I01 HX002475-01A2 from the US Veterans Administration.
                Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Meeting Presentations: This study was presented at the American Association for Thoracic Surgery 101st Annual Meeting; April 30, 2021; virtual.
                Article
                zoi210343
                10.1001/jamanetworkopen.2021.11613
                8160592
                34042991
                771ac988-cce2-44af-99e9-97799f08bf79
                Copyright 2021 Heiden BT et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 5 February 2021
                : 1 April 2021
                Categories
                Research
                Original Investigation
                Online Only
                Surgery

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