Dataset Information

Imagine a world without cancer.

ABSTRACT: BACKGROUND: Since the "War on Cancer" was declared in 1971, the United States alone has expended some $300 billion on research, with a heavy focus on the role of genomics in anticancer therapy. Voluminous data have been collected and analyzed. However, in hindsight, any achievements made have not been realized in clinical practice in terms of overall survival or quality of life extended. This might be justified because cancer is not one disease but a conglomeration of multiple diseases, with widespread heterogeneity even within a single tumor type. DISCUSSION: Only a few types of cancer have been described that are associated with one major signaling pathway. This enabled the initial successful deployment of targeted therapy for such cancers. However, soon after this targeted approach was initiated, it was subverted as cancer cells learned and reacted to the initial treatments, oftentimes rendering the treatment less effective or even completely ineffective. During the past 30 plus years, the cancer classification used had, as its primary aim, the facilitation of communication and the exchange of information amongst those caring for cancer patients with the end goal of establishing a standardized approach for the diagnosis and treatment of cancers. This approach should be modified based on the recent research to affect a change from a service-based to an outcome-based approach. The vision of achieving long-term control and/or eradicating or curing cancer is far from being realized, but not impossible. In order to meet the challenges in getting there, any newly proposed anticancer strategy must integrate a personalized treatment outcome approach. This concept is predicated on tumor- and patient-associated variables, combined with an individualized response assessment strategy for therapy modification as suggested by the patient's own results. As combined strategies may be outcome-orientated and integrate tumor-, patient- as well as cancer-preventive variables, this approach is likely to result in an optimized anticancer strategy. SUMMARY: Herein, we introduce such an anticancer strategy for all cancer patients, experts, and organizations: Imagine a World without Cancer.

SUBMITTER: Brucher BL

PROVIDER: S-EPMC3995593 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Imagine a world without cancer.

Brücher Björn L D M BL Lyman Gary G van Hillegersberg Richard R Pollock Raphael E RE Lordick Florian F Yang Han-Kwang HK Ushijima Toshikazu T Yeoh Khay-Guan KG Skricka Tomas T Polkowski Wojciech W Wallner Grzegorz G Verwaal Vic V Garofalo Alfredo A D'Ugo Domenico D Roviello Franco F Steinau Hans-Ulrich HU Wallace Timothy J TJ Daumer Martin M Maihle Nitah N Reid Thomas J TJ Ducreux Michel M Kitagawa Yuko Y Knuth Alexander A Zilberstein Bruno B Steele Scott R SR Jamall Ijaz S IS

BMC cancer 20140314

<h4>Background</h4>Since the "War on Cancer" was declared in 1971, the United States alone has expended some $300 billion on research, with a heavy focus on the role of genomics in anticancer therapy. Voluminous data have been collected and analyzed. However, in hindsight, any achievements made have not been realized in clinical practice in terms of overall survival or quality of life extended. This might be justified because cancer is not one disease but a conglomeration of multiple diseases, w ...[more]

PMID: 24629025

Similar Datasets

Project description:BackgroundBackground parenchymal enhancement (BPE) on breast magnetic resonance imaging (MRI) may be associated with breast cancer risk, but previous studies of the association are equivocal and limited by incomplete blinding of BPE assessment. In this study, we evaluated the association between BPE and breast cancer based on fully blinded assessments of BPE in the unaffected breast.MethodsThe Imaging and Epidemiology (IMAGINE) study is a multicenter breast cancer case-control study of women receiving diagnostic, screening, or follow-up breast MRI, recruited from three comprehensive cancer centers in the USA. Cases had a first diagnosis of unilateral breast cancer and controls had no history of or current breast cancer. A single board-certified breast radiologist with 12 years' experience, blinded to case-control status and clinical information, assessed the unaffected breast for BPE without view of the affected breast of cases (or the corresponding breast laterality of controls). The association between BPE and breast cancer was estimated by multivariable logistic regression separately for premenopausal and postmenopausal women.ResultsThe analytic dataset included 835 cases and 963 controls. Adjusting for fibroglandular tissue (breast density), age, race/ethnicity, BMI, parity, family history of breast cancer, BRCA1/BRCA2 mutations, and other confounders, moderate/marked BPE (vs minimal/mild BPE) was associated with breast cancer among premenopausal women [odds ratio (OR) 1.49, 95% CI 1.05-2.11; p = 0.02]. Among postmenopausal women, mild/moderate/marked vs minimal BPE had a similar, but statistically non-significant, association with breast cancer (OR 1.45, 95% CI 0.92-2.27; p = 0.1).ConclusionsBPE is associated with breast cancer in premenopausal women, and possibly postmenopausal women, after adjustment for breast density and confounders. Our results suggest that BPE should be evaluated alongside breast density for inclusion in models predicting breast cancer risk.

Project description:BackgroundThe understanding of the impact of COVID-19 in patients with cancer is evolving, with need for rapid analysis.AimsThis study aims to compare the clinical and demographic characteristics of patients with cancer (with and without COVID-19) and characterize the clinical outcomes of patients with COVID-19 and cancer.Methods and resultsReal-world data (RWD) from two health systems were used to identify 146 702 adults diagnosed with cancer between 2015 and 2020; 1267 COVID-19 cases were identified between February 1 and July 30, 2020. Demographic, clinical, and socioeconomic characteristics were extracted. Incidence of all-cause mortality, hospitalizations, and invasive respiratory support was assessed between February 1 and August 14, 2020. Among patients with cancer, patients with COVID-19 were more likely to be Non-Hispanic black (NHB), have active cancer, have comorbidities, and/or live in zip codes with median household income <$30 000. Patients with COVID-19 living in lower-income areas and NHB patients were at greatest risk for hospitalization from pneumonia, fluid and electrolyte disorders, cough, respiratory failure, and acute renal failure and were more likely to receive hydroxychloroquine. All-cause mortality, hospital admission, and invasive respiratory support were more frequent among patients with cancer and COVID-19. Male sex, increasing age, living in zip codes with median household income <$30 000, history of pulmonary circulation disorders, and recent treatment with immune checkpoint inhibitors or chemotherapy were associated with greater odds of all-cause mortality in multivariable logistic regression models.ConclusionRWD can be rapidly leveraged to understand urgent healthcare challenges. Patients with cancer are more vulnerable to COVID-19 effects, especially in the setting of active cancer and comorbidities, with additional risk observed in NHB patients and those living in zip codes with median household income <$30 000.

Dataset Information

Imagine a world without cancer.

Publications

Imagine a world without cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets