GLORIA

GEOMAR Library Ocean Research Information Access

X

Ihre E-Mail wurde erfolgreich gesendet. Bitte prüfen Sie Ihren Maileingang.

Leider ist ein Fehler beim E-Mail-Versand aufgetreten. Bitte versuchen Sie es erneut.

Vorgang fortführen?

Exportieren
Filter
  • American Association for Cancer Research (AACR)  (9)
  • Medizin  (9)
Materialart
Verlag/Herausgeber
  • American Association for Cancer Research (AACR)  (9)
Person/Organisation
Sprache
Erscheinungszeitraum
Fachgebiete(RVK)
  • Medizin  (9)
RVK
  • 1
    Online-Ressource
    Online-Ressource
    Abstract P5-14-07: Accuracy of psychosocial assessments in an online surgical decision aid developed for early breast cancer patients with resource and educational constraints
    American Association for Cancer Research (AACR) ; 2019
    In:  Cancer Research Vol. 79, No. 4_Supplement ( 2019-02-15), p. P5-14-07-P5-14-07
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 4_Supplement ( 2019-02-15), p. P5-14-07-P5-14-07
    Kurzfassung: Background: Women with early breast cancer routinely face a choice between breast conservation therapy and mastectomy, and assume agency through shared decision making. However, for women with lower socioeconomic power or education, barriers such as access to understandable information, involvement of family in decision making, and a decreased sense of autonomy inhibits this agency. To better empower this population, a simple to understand, online, self-administered, conjoint analysis based decision aid called “Navya Patient Preference Tool” (PPT) is developed to be used outside the physician encounter. PPT is unique in its incorporation of several psychological scales that assess potential confounders of participation in shared decision making. Methodology: This is a pre-planned analysis of the reliability and validity of the psychological scales used in all three arms of an IRB approved randomized controlled trial to assess PPT. Women with operable node negative breast cancer eligible for BCT or MRM at one of Asia's largest academic tertiary cancer centers were eligible. PPT trial consists of an initial conjoint analysis questionnaire analyzing implicit preferences for breast conservation given to the intervention arms. The following psychological scales were given to all patients regardless of randomization: Autonomy Preference Index (API), Traditional-Egalitarian Gender Roles (TEGR), Caregiving Role, Brief Resiliency Scale (BRS), Appearances Scale, and Decisional Conflict Scale (DCS). Cronbach's alpha as a measure of internal reliability for all scales, and correlations of scores with known demographic trends as a measure of external validity are calculated. Results: Of the 102 patients enrolled, 30 completed PPT in English, 39 in Hindi, and 33 in Marathi, (vernaculars). 69/102 were in middle and lower socioeconomic groups (Kuppuswamy Index). 53/102 had completed less than high school education. Internal reliability of all scales were high, with Cronbach's alpha above 0.7: API 0.74, TEGR 0.78, Caregiving 0.7, BRS 0.7, Appearance 0.84. DCS was highly reliable at 0.91, and is the primary outcome measure for the RCT. Correlations in the dataset met those expected in real world data, suggesting external validity. For e.g., education was inversely correlated with traditional gender roles on TEGR (R -0.4, p & lt;0.01), and positively correlated with resilience on BRS (R 0.228, p & lt;0.05). Individual scale items that are unrealistic were not chosen by any of the 102 respondents (e.g.,. My doctor should not participate in my medical decisions), substantiating nuanced reading. 85% of patients “Strongly Agreed” on a 1-5 Likert scale that “The survey questions were easy to understand” (mean score 1.18/5. SD 0.4). Conclusions: Women with limited education and low socioeconomic status complete the online, self administered PPT outside of a physician encounter, with high internal reliability and external validity. Decision Aids such as Navya PPT, which account for psychosocial confounders of agency, have the potential to benefit women otherwise marginalized from shared decision making. Citation Format: Joshi S, Ramarajan L, Ramarajan N, Srivastava G, Begum F, Deshpande O, Tondare A, Nair N, Parmar V, Gupta S, Badwe RA. Accuracy of psychosocial assessments in an online surgical decision aid developed for early breast cancer patients with resource and educational constraints [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-14-07.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.SABCS18-P5-14-07
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2019
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 2
    Online-Ressource
    Online-Ressource
    Abstract P4-10-02: Validation of a clinical informatics system for online multidisciplinary expert opinions: Mapping treatment recommendations to the NCCN resource-Stratified framework
    American Association for Cancer Research (AACR) ; 2018
    In:  Cancer Research Vol. 78, No. 4_Supplement ( 2018-02-15), p. P4-10-02-P4-10-02
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 4_Supplement ( 2018-02-15), p. P4-10-02-P4-10-02
    Kurzfassung: Background: Most cancer patients in Low and Middle Income Countries (LMIC) cannot afford effective, expensive, evidence based therapies. Therefore, oncologists must tailor treatment plans to individual resource constraints. To support this, NCCN has created a Resource-Stratified Framework® (NCCN-RSF), which is an evidence-based four-tier prioritization scheme. Further, only a fraction of patients in LMIC have ready access to oncologists. In India, there are only ˜1600 oncologists for 1.8 million patients. To bridge this gap, Navya's clinical informatics based mobile ExpertApp combines learning from evidence, prior tumor board decisions, patient resource constraints, and quick review from TMC NCG oncologists to recommend tailored treatment plans to patients via an online expert opinion service. 11865 patients in 22 LMIC have reached out to receive an online expert opinion through Navya (ASCO 2017). This study maps Navya to NCCN-RSF as an evidence-based index for resource-sensitive treatment selection. Methods: All breast cancer patients who received an online expert opinion from TMC NCG Navya between July 1st 2014 and April 30th 2017 were included. Navya systematically gathered information on patient resource constraints (such as affordability for Trastuzumab). Navya recommendations (breast and nodal surgery, radiation site and fractionation, drug and dose density etc.) were mapped to NCCN-RSF resource tiers (Basic, Core, Enhanced, Parent guideline). Reasons were categorized for Navya recommendations not present in NCCN-RSF. Results: 616 patients (36.3% metastatic), mostly from India, received 1203 recommendations. At the specific treatment protocol level, 88.3% of Navya recommendations mapped with at least one NCCN-RSF resource tier (Table 1). 78.5% mapped to the Enhanced tier. Only 8.6% of recommendations mapped to Parent guidelines, and did not require tailoring for resource constraints. Fewer than 2% recommendations mapped to Core and none to Basic. 11.7% recommendations were not present in NCCN-RSF, for minor reasons such as substitution of a drug within the same class (35.8%) (e.g., Epirubicin for Adriamycin), dose dense protocols (14.3%) (e.g., 3 weekly Paclitaxel vs weekly Paclitaxel), and recommending Trastuzumab for less than a year for patients unable to afford year long therapy (14.3%), currently not included in NCCN-RSF. Table 1- Mapping Navya to NCCN RSFNCCN RSF TiersHIGH LEVEL: Multimodality treatment and sequencing (1203)INTERMEDIATE: Within modality treatment categories (1188)GRANULAR: Specific treatment protocols (1140)E.g.Neoadjuvant vs Adjuvant ChemoAnthracycline vs TaxaneHypofractionation vs Standard XRTAt least one Tier98.8%±0.696%±1.188.3%±2Enhanced94.4%±1.391%±1.778.5%±2.7Core1.9%±5.61.2%±5.71.2%±5.8Parent NCCN2.4%±5.63.8%±5.68.6%±5.5 Conclusion: Navya's treatment recommendations are sensitive to resource constraints and map to peer reviewed and evidence based NCCN RSF, primarily at the Enhanced tier. Navya's clinical informatics based online service scales access to resource constrained treatment selection for large numbers of patients in LMIC without easy access to oncologists. Citation Format: Badwe RA, Gupta S, Feldman N, Pramesh CS, Ramarajan N, Srivastava G, Nair N, Anderson BO. Validation of a clinical informatics system for online multidisciplinary expert opinions: Mapping treatment recommendations to the NCCN resource-Stratified framework [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-10-02.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.SABCS17-P4-10-02
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2018
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 3
    Online-Ressource
    Online-Ressource
    Abstract P1-14-01: Building an experience engine to make cancer treatment decisions using machine learning
    American Association for Cancer Research (AACR) ; 2017
    In:  Cancer Research Vol. 77, No. 4_Supplement ( 2017-02-15), p. P1-14-01-P1-14-01
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 4_Supplement ( 2017-02-15), p. P1-14-01-P1-14-01
    Kurzfassung: Introduction: Experts at tertiary care centers provide solutions to complex cases not addressed by high quality evidence. They intuitively retrieve patterns from years of experience to make treatment decisions. Short of personal consultations, there is no way to access this vast “experience database.” Experience Engine (XE) is a machine learning solution to structure experiential knowledge relevant for decision making, derive a similarity metric for patients who have received similar treatments, and predict treatment decisions that experts are likely to recommend. Methods: 277 patient histories relating to 743 breast cancer tumor board decisions at two tertiary care centers were abstracted as the training set for machine learning. 161 distinct histories relating to 496 decisions for a separate expert opinion service at one of the centers was the holdout test set. Data was structured into 690 features based on a novel ontology designed specifically for breast cancer decision making. To uncover nonlinear similarities, (for example, treatments for younger patients with multiple comorbidities and elderly patients may be similar), treatment decisions were grouped by timing and modality into 13 groups, such as primary surgery, 1st line palliative chemotherapy, etc. Similarity metric was derived using machine learning on the training set. The target for prediction was the specific treatment decision i.e. TAC or another adjuvant regimen. The primary endpoint was percent accuracy of agreement between XE's predicted decision and experts' actual decision in the holdout test set. Multiple similarity distance metrics including Bhattacharya, Eskin, Goodall, etc., and multiclass classification algorithms such as Extreme Gradient Boosted Trees, Support Vector Machines, etc., were systematically evaluated to arrive at the algorithms that best fit each treatment group. Results: The winning XE algorithms were 71% to 89% accurate for the various treatment groups, in predicting the actual treatment decisions recommended by the experts. The most frequent treatments recommended across all groups were standard evidence based therapies, as are often recommended by experts. For instance, when XE recommended standard adjuvant therapies for Her2- patients, it was 88% to 97% accurate. When XE recommended nonstandard therapies for the same treatment group, it was 72% to 90% accurate, related to larger number of nonstandard therapies within each treatment group and smaller samples of patients who underwent each type of nonstandard therapy. XE learned to weigh features relating to comorbidities and toxicities when recommending nonstandard therapies. Conclusion: Machine learning on a structured database of past treatment decisions made by experts, can yield a predicted treatment decision that an expert is likely to recommend for a new patient. By including complex decisions that consider toxicities and morbidities, a rich source of knowledge can be created. Despite the limited dataset, XE learned features that experts strongly consider when making decisions. XE has the potential to analyze variations in decision making at expert practices, assess when to recommend nonstandard therapies, and serve as a training tool for new oncologists to make expert grade treatment decisions. Citation Format: Ramarajan N, Gupta S, Perry P, Srivastava G, Kumbla A, Miller J, Feldman N, Nair N, Badwe RA. Building an experience engine to make cancer treatment decisions using machine learning [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-14-01.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.SABCS16-P1-14-01
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2017
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 4
    Online-Ressource
    Online-Ressource
    Targeting Aldose Reductase: A Novel Strategy in Treating Endocrine Resistance Using Combination Therapy.
    American Association for Cancer Research (AACR) ; 2009
    In:  Cancer Research Vol. 69, No. 24_Supplement ( 2009-12-15), p. 67-67
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 69, No. 24_Supplement ( 2009-12-15), p. 67-67
    Kurzfassung: Breast cancer is the most commonly diagnosed form of cancer in women. Among breast cancer patients about 2/3 are initially hormone sensitive or estrogen receptor (ER) positive and respond to endocrine therapy. Aromatase inhibitors (AI's) are superior class of hormonal therapeutic agents effectively control ER positive breast cancer in postmenopausal women. Acquired resistance to AI's is expected to be an emerging serious problem in clinics and recent studies have shown that tumors use adaptive signaling mechanisms to overcome AI sensitivity. Thus there is an urgent need for newer treatment modalities. Combination of endocrine and non endocrine agents that block these signaling pathways may prevent or delay the adaptive mechanism and thereby onset of resistance to hormonal therapy. In our study we have found that Fidarestat, an aldose reductase (enzyme which catalyzes the rate limiting step of glucose to fructose or sorbitol formation in polyol pathway) inhibitor effectively re-sensitize letrozole resistant LTLT-Ca breast cancer cells to letrozole. 1µM of fidarestat + 1uM letrozole was found very effective in inducing maximum cell death in LTLT-Ca cells when compared to fidarestat alone. The combination treatment not only restored ER-α levels but also down regulated HER2/MAPK signaling proteins. Aldose reductase siRNA (100nM)- treated MCF-7/Aro and MCF-7 cells upregulated ER-α in western blot and ER-functionality assays. On the other hand in aldose reductase-siRNA- treated LTLT-Ca cells, ER-α levels were down- regulated as in fidarestat treatment. Pretreatment of LTLT-Ca with fidarestat for one week showed reduced proliferation of cells and the effect was maintained until four passages with 1µM letrozole alone. Fidarestat treatment up-regulated E2-mediated transcription in LTLT-Ca cells. In order to enhance the efficacy and targeted delivery of fidarestat in LTLT–Ca cells we have used a nanoparticle-based therapeutic formulation. Folate receptor, highly expressed on epithelial carcinomas, could be a potential molecular target for tumor selective drug delivery. Physcio-chemically well characterized Fidarestat–folate nanoparticles (FFNP's) were prepared to increase the tumor selective intracellular delivery. FFNP's were found superior in exerting cytotoxicity when compared to fidarestat alone. Combination therapy was equally effective in controlling LTLT-Ca cell growth using xenograft model. Taken together, the increased glucose metabolism in LTLT-Ca cells may be critically contributing to chemotherapeutic resistance by increasing drug metabolism and decreasing uptake. Hence targeting aldose reductase in endocrine resistance may be attractive alternative to increase the sensitivity of hormonal therapy. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 67.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/0008-5472.SABCS-09-67
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2009
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 5
    Online-Ressource
    Online-Ressource
    Abstract P5-05-10: Estrogen receptor β suppresses metastasis of inflammatory breast cancer by regulating cell cytoskeleton and cytokine signaling
    American Association for Cancer Research (AACR) ; 2019
    In:  Cancer Research Vol. 79, No. 4_Supplement ( 2019-02-15), p. P5-05-10-P5-05-10
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 4_Supplement ( 2019-02-15), p. P5-05-10-P5-05-10
    Kurzfassung: Inflammatory breast cancer (IBC) is the most lethal form of breast cancer that accounts for about 10% of breast cancer mortality annually in US. Poor prognosis is largely due to the high propensity of IBC tumors to develop distant metastasis that occurs directly from the gland epithelium and through lymphatic invasion in which dermal lymphatics are filled with tumor emboli. Owing to the complex metastatic process, the molecular basis of IBC aggressiveness is poorly understood, and no specific therapeutic target has been identified. Despite the lack of estrogen receptor α (ERα) in the majority of IBC tumors, estrogen may still play a role in these cancers through pathways that involve ERβ. Our tissue staining reveals expression of ERβ in more than 50% of IBCs that is reproduced in IBC cell lines. Furthermore, analysis of IBC datasets indicates correlation of receptor expression with good prognosis. We studied this association in preclinical models of IBC by knocking out ERβ in IBC cells. This promotes migration and invasion through cytoskeleton remodeling whereas re-expression of the receptor in knockout cells restores the cytoskeletal structure and migration to the levels of control cells. Consistent with increased migration, deletion of ERβ activates large gene networks of cell de-differentiation and cytokine synthesis that trigger tumor microenvironment responses to promote the motile phenotype of IBC cells. In contrast, ligands that activate the receptor inhibit signaling that contributes to metastasis in IBC. Analysis of an orthotopic xenograft model shows that IBC tumors lacking ERβ have higher propensity for metastasis compared with the ERβ-proficient tumors supporting the anti-metastatic activity of the receptor. Our findings point towards a role of ERβ in preventing distant metastases by inhibiting dissemination of IBC cells and maintaining the integrity of emboli. This function combined with distinct expression indicates the potential of ERβ to represent a unique prognostic marker and therapeutic target that can be utilized to repress IBC metastasis and eliminate its associated mortality. Citation Format: Thomas C, Karagounis I, Srivastava RK, Kumar S, Karar J, Chao H-H, Kazimierczak A, Bado I, Nikolos F, Leli N, Koumenis C, Krishnamurthy S, Ueno NT, Chakrabarti R, Maity A. Estrogen receptor β suppresses metastasis of inflammatory breast cancer by regulating cell cytoskeleton and cytokine signaling [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-05-10.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.SABCS18-P5-05-10
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2019
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 6
    Online-Ressource
    Online-Ressource
    Abstract 2691: Genome-wide association study identifies two susceptibility loci that modify radiation-related risk for breast cancer after childhood cancer: A report from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort
    American Association for Cancer Research (AACR) ; 2016
    In:  Cancer Research Vol. 76, No. 14_Supplement ( 2016-07-15), p. 2691-2691
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 14_Supplement ( 2016-07-15), p. 2691-2691
    Kurzfassung: Background: Childhood cancer survivors treated with chest radiotherapy have substantially elevated risk for developing breast cancer. Although numerous breast cancer susceptibility variants have been established, genetic predisposition for breast cancer after childhood cancer remains poorly understood. Methods: We conducted the first genome-wide association study of subsequent breast cancer in female childhood cancer survivors within two large-scale cohorts with detailed treatment data and systematic, long-term follow-up: the Childhood Cancer Survivor Study [CCSS; 178 breast cancer cases, 2200 controls (survivors without subsequent neoplasm) of European descent] and the St. Jude Lifetime Cohort (SJLIFE; 29 cases, 574 controls). Genotyping on the Illumina HumanOmni5MExome (CCSS) or Affymetrix 6.0 (SJLIFE) array and imputation based on the 1000 Genomes Project yielded & gt;16 million high quality genotyped or imputed variants available in both studies. Assuming an additive genetic model, we used multivariate Cox regression to quantify the effect of each variant in the overall population and stratified by receipt of ≥10 Gray (Gy) or & lt;10 Gy radiation exposure to the chest. Results: We identified two loci associated with breast cancer risk among children who received ≥10 Gy radiation to the chest (131 cases, 493 controls): one at 1q41 [rs4342822, risk allele frequency (RAF) = 0.46 in controls, pooled per allele hazard ratio (HR) = 1.94, 95% confidence interval (CI) = 1.50-2.51, Pexact = 1.20×10−8] and another at 11q23 (rs74949440, RAF = 0.02 in controls, HR = 3.71, 95%CI = 2.18-6.32, Pexact = 2.00×10−9). Neither locus was associated with breast cancer risk among children who received & lt;10 Gy radiation to the chest (69 cases, 2144 controls; rs4342822: HR = 1.03, 95%CI = 0.75-1.44; rs74949440: HR = 1.21, 0.41-3.54). Results were consistent in the two studies, and the associations did not appear to be related to type of first primary childhood cancer. Both loci fall in or near biologically plausible candidate genes: the variant rs4342822 lies near PROX1, which is amplified in & gt;10% of breast cancers in The Cancer Genome Atlas data. The variant rs74949440 is intronic to TAGLN, whose expression levels have been associated with breast cancer prognosis and altered cell death resistance following irradiation in human carcinoma cell lines. Conclusion: These findings represent the first evidence outside of identified high-risk cancer susceptibility genes that certain individuals are genetically predisposed to developing breast cancer after radiotherapy and suggest that radiation exposure may interact with germline genetics to modify breast cancer risk. Citation Format: Lindsay M. Morton, Joshua N. Sampson, Gregory T. Armstrong, Ting-Huei Chen, Melissa Hudson, Eric Karlins, Casey L. Dagnall, Shenchao Li, Carmen L. Wilson, Kumar Srivastava, Wei Liu, Guolian Kang, Kevin Oeffinger, Tara O. Henderson, Chaya S. Moskowitz, Todd M. Gibson, Diana M. Merino, Jeannette R. Wong, Sue Hammond, Joseph P. Neglia, Lucie M. Turcotte, Jeremy Miller, Laura Bowen, William A. Wheeler, Wendy M. Leisenring, John A. Whitton, Laurie Burdette, Belynda D. Hicks, Mitchell J. Machiela, Aurelie Vogt, Zhaoming Wang, Meredith Yeager, Geoffrey Neale, Matthew Lear, Louise C. Strong, Yutaka Yasui, Marilyn Stovall, Rita E. Weathers, Susan A. Smith, Rebecca Howell, Stella M. Davies, Gretchen A. Radloff, Amy Berrington de González, Peter D. Inskip, Preetha Rajaraman, Joseph F. Fraumeni, Smita Bhatia, Stephen J. Chanock, Margaret A. Tucker, Leslie L. Robison. Genome-wide association study identifies two susceptibility loci that modify radiation-related risk for breast cancer after childhood cancer: A report from the Childhood Cancer Survivor Study and St. Jude Lifetime Cohort. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2691.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2016-2691
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2016
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 7
    Online-Ressource
    Online-Ressource
    Abstract P3-03-10: Penfluridol reduces paclitaxel resistance in breast cancer by inhibiting HER2/β-catenin signaling
    American Association for Cancer Research (AACR) ; 2017
    In:  Cancer Research Vol. 77, No. 4_Supplement ( 2017-02-15), p. P3-03-10-P3-03-10
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 4_Supplement ( 2017-02-15), p. P3-03-10-P3-03-10
    Kurzfassung: This abstract was not presented at the symposium.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.SABCS16-P3-03-10
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2017
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 8
    Online-Ressource
    Online-Ressource
    Immunomodulatory Activity of Nivolumab in Metastatic Renal Cell Carcinoma
    American Association for Cancer Research (AACR) ; 2016
    In:  Clinical Cancer Research Vol. 22, No. 22 ( 2016-11-15), p. 5461-5471
    Details
    In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 22, No. 22 ( 2016-11-15), p. 5461-5471
    Kurzfassung: Purpose: Nivolumab, an anti-PD-1 immune checkpoint inhibitor, improved overall survival versus everolimus in a phase 3 trial of previously treated patients with metastatic renal cell carcinoma (mRCC). We investigated immunomodulatory activity of nivolumab in a hypothesis-generating prospective mRCC trial. Experimental Design: Nivolumab was administered intravenously every 3 weeks at 0.3, 2, or 10 mg/kg to previously treated patients and 10 mg/kg to treatment-naïve patients with mRCC. Baseline and on-treatment biopsies and blood were obtained. Clinical activity, tumor-associated lymphocytes, PD-L1 expression (Dako immunohistochemistry; ≥5% vs. & lt;5% tumor membrane staining), tumor gene expression (Affymetrix U219), serum chemokines, and safety were assessed. Results: In 91 treated patients, median overall survival [95% confidence interval (CI)] was 16.4 months [10.1 to not reached (NR)] for nivolumab 0.3 mg/kg, NR for 2 mg/kg, 25.2 months (12.0 to NR) for 10 mg/kg, and NR for treatment-naïve patients. Median percent change from baseline in tumor-associated lymphocytes was 69% (CD3+), 180% (CD4+), and 117% (CD8+). Of 56 baseline biopsies, 32% had ≥5% PD-L1 expression, and there was no consistent change from baseline to on-treatment biopsies. Transcriptional changes in tumors on treatment included upregulation of IFNγ-stimulated genes (e.g., CXCL9). Median increases in chemokine levels from baseline to C2D8 were 101% (CXCL9) and 37% (CXCL10) in peripheral blood. No new safety signals were identified. Conclusions: Immunomodulatory effects of PD-1 inhibition were demonstrated through multiple lines of evidence across nivolumab doses. Biomarker changes from baseline reflect nivolumab pharmacodynamics in the tumor microenvironment. These data may inform potential combinations. Clin Cancer Res; 22(22); 5461–71. ©2016 AACR.
    Materialart: Online-Ressource
    ISSN: 1078-0432 , 1557-3265
    URL: Article
    DOI: 10.1158/1078-0432.CCR-15-2839
    RVK:
    XA 36791
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2016
    ZDB Id: 1225457-5
    ZDB Id: 2036787-9
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
  • 9
    Online-Ressource
    Online-Ressource
    Abstract P3-16-01: Responding at patient's time of need: Scaling rapid access to evidence-based treatment plans
    American Association for Cancer Research (AACR) ; 2019
    In:  Cancer Research Vol. 79, No. 4_Supplement ( 2019-02-15), p. P3-16-01-P3-16-01
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 79, No. 4_Supplement ( 2019-02-15), p. P3-16-01-P3-16-01
    Kurzfassung: Background: Cancer patients worldwide feel intense anxiety, often racing to start treatments at non expert centers. Further, imbalanced oncologist to patient ratios (˜1600: 1.8 M in India, ˜23,000: 15M in USA), impedes access to expertise. We study the impact of rapid evidence based expert treatment plans in relieving patient anxiety. Navya, a health services technology, generates personalized treatment plans that maps within NCCN Resource Stratified Guidelines [SABCS 2017]. This is vetted on mobile by oncologists at tertiary centers like TMC NCG to provide expert opinion reports to patients. Since 2015, ˜19,457 patients from 57 countries have reached out for an online opinion. On the ground, 78% of patients received evidence based treatments recommended by Navya [ASCO 2017] . Methods: To assess impact of timeliness, a prospective series of patients (from Sep '17 to April '18) were asked: “Were you relieved to receive expert opinion report in [x] days?” “Does it matter to you to receive expert opinion report in 1 day?” To assess time savings, preliminary reports with treatment options from NCCN and TMC NCG guidelines were shared with patients who matched all guidelines criteria. Subsequently, expert opinion reports were shared as usual. Results: 543/701 patients responded to phone follow-up. 97% [± 3.2] were relieved to receive expert opinion reports in 1-2 days (103/106) vs 83% [± 3.8 ] for 3+ days (365/437). Of those not relieved by 3+ day turnaround, 83% stated that it would matter to receive expert opinion reports in 1 day (60/72). The first 300 preliminary reports shared in median time of 3.37 hours, resulted in 90% time savings vs expert opinion reports. On 10% of the preliminary reports, experts added information such as de-/escalating therapy (18/31), and additional diagnostic tests (6/31). Conclusions: Navya relieves patient anxieties by responding at the time of need with evidence based treatment plans. Scaling such health services technologies to patients worldwide is feasible. Citation Format: Ramarajan N, Srivastava R, Begum F, Gupta S, Pramesh C, Badwe R. Responding at patient's time of need: Scaling rapid access to evidence-based treatment plans [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-16-01.
    Materialart: Online-Ressource
    ISSN: 0008-5472 , 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.SABCS18-P3-16-01
    RVK:
    XA 36000
    RVK:
    XA 10000
    Sprache: Englisch
    Verlag: American Association for Cancer Research (AACR)
    Publikationsdatum: 2019
    ZDB Id: 2036785-5
    ZDB Id: 1432-1
    ZDB Id: 410466-3
    Standort Signatur Einschränkungen Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
Schließen ⊗
Diese Webseite nutzt Cookies und das Analyse-Tool Matomo. Weitere Informationen finden Sie hier...