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Response adapted de-escalation of neo-adjuvant therapy for intermediate risk HER2-positive early breast cancer: an institutional experience
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.103727
T. Talbot, F. Rehman, L. Kenny, V. Harding, O. Hatcher, S. Cleator
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引用次数: 0
A comprehensive overview of a single-institutional (University College London Hospital) experience with CDK4/6 inhibitors in ER+/HER2- metastatic breast cancer
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.103728
T.J. Walsh, L.M. Vallodolid, K. Gayford, R. Nayar, K. DeSouza, R. Roylance
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引用次数: 0
Quality of Decision Making in Radiation Oncology 放射肿瘤学决策的质量。
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.02.001
S.K. Vinod , R. Merie , S. Harden
High-quality decision making in radiation oncology requires the careful consideration of multiple factors. In addition to the evidence-based indications for curative or palliative radiotherapy, this article explores how, in routine clinical practice, we also need to account for many other factors when making high-quality decisions. Foremost are patient-related factors, including preference, and the complex interplay between age, frailty and comorbidities, especially with an ageing cancer population. Whilst clinical practice guidelines inform our decisions, we need to account for their applicability in different patient groups and different resource settings. With particular reference to curative-intent radiotherapy, we explore decisions regarding dose fractionation schedules, use of newer radiotherapy technologies and multimodality treatment considerations that contribute to personalised patient-centred care.
放射肿瘤学的高质量决策需要仔细考虑多种因素。除了治疗性或姑息性放疗的循证适应症外,本文还探讨了在常规临床实践中,我们如何在做出高质量决策时还需要考虑许多其他因素。最重要的是与患者相关的因素,包括偏好,以及年龄、体弱和合并症之间复杂的相互作用,尤其是在癌症患者老龄化的情况下。虽然临床实践指南为我们的决策提供了参考,但我们也需要考虑其在不同患者群体和不同资源环境中的适用性。特别是在治疗性放射治疗方面,我们将探讨有关剂量分次计划的决策、较新放射治疗技术的使用以及多模式治疗的注意事项,这些都有助于实现以患者为中心的个性化治疗。
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引用次数: 0
Concurrent Chemoradiotherapy versus Radiotherapy Alone in the Treatment of Stage II and T3N0M0 Nasopharyngeal Carcinoma: A Systematic Review and Meta-Analysis 治疗 II 期和 T3N0M0 鼻咽癌的同期化放疗与单独放疗:系统回顾与元分析》(Concurrent Chemoradiotherapy versus Radiotherapy Alone in the Treatment of Stage II and T3N0M0 Nasopharyngeal Carcinoma: A Systematic Review and Meta-Analysis.
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.10.004
H. Zeng, H. Wang, S. Liu, X. Xu

Aims

The efficacy of concurrent chemoradiotherapy (CCRT) for Stage II and T3N0 nasopharyngeal carcinoma (NPC), particularly during the shift from two-dimensional conventional radiotherapy (2DCRT) to intensity-modulated radiotherapy (IMRT) is debated.Therefore this study aims to systematically evaluate and meta-analyze survival benefits of CCRT versus radiotherapy alone for Stage II and T3N0 NPC, stratified by radiotherapy techniques.

Materials and methods

As of April 1, 2024, we conducted an exhaustive literature search across databases such as PubMed, Embase, Cochrane Library, and Web of Science, with the aim of identifying and screening studies that compare the efficacy of CCRT versus radiotherapy alone in the treatment of Stage II and T3N0 NPC.

Results

A total of 10 studies encompassing 5015 patients were included in this comprehensive analysis. The findings indicate that, apart from progression-free survival (PFS), CCRT did not improve survival outcomes, including overall survival (OS), distant metastasis-free survival (DMFS), local recurrence-free survival (LRRFS), and failure-free survival (FFS), with all P values exceeding 0.05. Concurrently, the incidence of grade ≥3 adverse events associated with CCRT was significantly elevated (odds ratio [OR] = 3.77, 95% confidence interval [CI] = 2.75–5.15, P < 0.0001). Subgroup analysis revealed that, compared with RT, the combination of 2DCRT with concurrent chemotherapy significantly improved OS (hazard ratio [HR] = 0.57, 95% CI = 0.46–0.71, P < 0.00001), PFS (HR = 0.65, 95% CI=0.53–0.78, P < 0.00001), DMFS (HR = 0.54, 95% CI = 0.37–0.79, P = 0.002), and LRRFS (HR = 0.63, 95% CI = 0.49–0.82, P = 0.0005). In contrast, the combination of IMRT with concurrent chemotherapy failed to demonstrate improvements in OS, PFS, DMFS, or LRRFS, with all P values exceeding 0.05.

Conclusion

In contrast with RT, CCRT did not enhance survival in stage II and T3N0 NPC patients, yet caused more adverse reactions. 2DCRT combined with concurrent chemotherapy significantly improved OS, PFS, DMFS, and LRRFS, while IMRT with concurrent chemotherapy showed no clinical benefits.
目的:对于II期和T3N0鼻咽癌(NPC)的同期化学放疗(CCRT)疗效,尤其是在从二维常规放疗(2DCRT)向调强放疗(IMRT)转变的过程中的疗效存在争议:截至2024年4月1日,我们在PubMed、Embase、Cochrane Library和Web of Science等数据库中进行了详尽的文献检索,旨在识别和筛选在治疗II期和T3N0 NPC时比较CCRT与单纯放疗疗效的研究:本次综合分析共纳入了 10 项研究,涵盖 5015 名患者。研究结果表明,除无进展生存期(PFS)外,CCRT并未改善生存结果,包括总生存期(OS)、无远处转移生存期(DMFS)、无局部复发生存期(LRRFS)和无失败生存期(FFS),所有P值均超过0.05。同时,与CCRT相关的≥3级不良事件的发生率显著升高(几率比[OR]=3.77,95%置信区间[CI]=2.75-5.15,P<0.0001)。亚组分析显示,与RT相比,2DCRT联合同期化疗可明显改善OS(危险比[HR] = 0.57,95% CI = 0.46-0.71,P<0.00001)、PFS(HR=0.65,95% CI=0.53-0.78,P<0.00001)、DMFS(HR=0.54,95% CI=0.37-0.79,P=0.002)和LRRFS(HR=0.63,95% CI=0.49-0.82,P=0.0005)。相比之下,IMRT与同期化疗的组合未能改善OS、PFS、DMFS或LRRFS,所有P值均超过0.05:与RT相比,CCRT并不能提高II期和T3N0鼻咽癌患者的生存率,但会引起更多不良反应。2DCRT 联合同期化疗可显著改善 OS、PFS、DMFS 和 LRRFS,而 IMRT 联合同期化疗则无临床益处。
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引用次数: 0
The Evidence for Low-level Laser Therapy for Oral Mucositis in Head and Neck Cancer Radiotherapy 低水平激光治疗头颈部肿瘤放疗中口腔黏膜炎的证据。
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.103731
J. O'Hara , M.S. Iqbal
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引用次数: 0
Dose Recommendations for Prostrate-specific Membrane Antigen Positron Emission Tomography (PSMA PET) Guided Boost Irradiation to Lymphatic Tissue in Prostate Adenocarcinoma 前列腺腺癌患者前列腺特异性膜抗原正电子发射断层扫描(PSMA PET)引导下淋巴组织增强照射的剂量建议。
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.103730
K. Martell , C. Kirkby

Aims

Prostrate-specific membrane antigen positron emission tomography (PSMA-PET) imaging has led to an increase in identifiable small volume metastatic disease in prostate adenocarcinoma. There is clinical equipoise in how to treat these using radiotherapy regimens. The aim of this study is to determine an adequate dosing regimen for small volume lymphatic metastases in prostate adenocarcinoma.

Materials and methods

The authors first estimated the cell count of small volume metastases in prostate adenocarcinoma and then used a Poisson distribution-based estimation of the tumour control probability distribution, the required doses for 95% and 99% probabilities of tumour sterilisation were calculated using the linear quadratic formula.

Results

Lymph node metastases of 3, 5, and 10 mm diameter were estimated to harbour 1.4, 6.5, and 52.3 million clonogens, respectively. When attempting for a 95% tumour control probability, estimated BEDs of 116.5, 127.0, and 141.1Gy were required. This translated to doses of 26.0, 27.3, and 29.0Gy in 5 fraction regimens. When attempting for a 99% tumour control probability, estimated biological effective doses (BEDs) of 127.6, 138.1, and 152.2 Gy were required. This translated to doses of 27.4, 28.6, and 30.2 Gy in 5 fraction regimens.

Conclusion

In prostate cancers with small-volume metastatic disease, doses can be adjusted according to tumour size without likely to compromise tumour control. This would have positive implications on radiotherapy planning and possibly lead to decreased risks of toxicity in scenarios where planning difficulty is encountered. Clinical evaluation of efficacy and safety for these dose regimens is warranted.
目的:前列腺特异性膜抗原正电子发射断层扫描(PSMA-PET)成像导致前列腺癌中可识别的小体积转移性疾病的增加。在如何使用放射治疗方案治疗这些疾病方面存在临床平衡。本研究的目的是确定前列腺腺癌小体积淋巴转移的适当给药方案。材料和方法:作者首先估计前列腺腺癌小体积转移的细胞计数,然后使用基于泊松分布的肿瘤控制概率分布估计,使用线性二次公式计算95%和99%肿瘤灭菌概率所需的剂量。结果:直径为3mm、5mm和10mm的淋巴结转移估计分别含有140万个、650万个和5230万个克隆原。当试图达到95%的肿瘤控制概率时,估计需要116.5、127.0和141.1Gy的剂量。这转化为26.0、27.3和29.0Gy的剂量,分为5个部分方案。当尝试99%的肿瘤控制概率时,估计的生物有效剂量(BEDs)为127.6、138.1和152.2 Gy。这转化为27.4、28.6和30.2 Gy的剂量,分为5个部分方案。结论:对于小体积转移性前列腺癌,可以根据肿瘤大小调整剂量,而不会影响肿瘤的控制。这将对放射治疗计划产生积极影响,并可能在遇到计划困难的情况下降低毒性风险。对这些剂量方案的有效性和安全性进行临床评估是必要的。
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引用次数: 0
The prognostic value of LDH in patients with good risk metastatic seminoma treated with single-agent Carboplatin AUC 10
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.10.013
N. Abdul Aziz , S. Ganguli , N.G. Kenrick , P. Rajan , A. Sharma , J. Shamash
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引用次数: 0
Leading from the front: Real-world treatment of metastatic hormone-sensitive prostate cancer in the Northwest of England
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.10.024
A. Singh, Z. Arif, A. Birtle
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引用次数: 0
Real-world data (RWD) from patients with triple-negative breast cancer (TNBC) receiving pembrolizumab with neoadjuvant chemotherapy (NACT+P) versus NACT alone
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.103720
J. McKeon, E. Daniels, L. Gibbs, C. Comins, J. Jenkins, T. Strawson-Smith, V. Mohan, M.H. Allah, J. Braybrooke, T. Robinson
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引用次数: 0
The Use of Artificial Intelligence Technologies in Cancer Care 人工智能技术在癌症护理中的应用。
IF 3.2 3区 医学 Q2 ONCOLOGY Pub Date : 2025-02-01 DOI: 10.1016/j.clon.2024.09.003
P.J. Hoskin
Artificial intelligence (AI) is already an essential tool in the handling of large data sets in epidemiology and basic research.
Significant contributions to radiological diagnosis are emerging alongside increasing use of digital pathology. The future lies in integrating this information together with clinical data relevant to each individual patient. Linkage with clinical protocols will enable personalized management options to be presented to the oncologist of the future.
Radiotherapy has the distinction of being the first to have a National Institute for Health and Care Excellence (NICE)-approved AI-based recommendation. There is the opportunity to revolutionize the workflow with many tasks currently undertaken by clinicians taken over by AI-based systems for volume outlining, planning, and quality assurance.
Education and training will be essential to understand the AI processes and inputs. Clinicians will however have to feel confident interrogating the AI-derived information and in communicating AI-derived treatment plans to patients.
人工智能(AI)已成为流行病学和基础研究领域处理大型数据集的重要工具。随着数字病理学应用的不断增加,人工智能对放射诊断的重大贡献也正在显现。未来的关键在于将这些信息与每个病人的相关临床数据整合在一起。与临床方案的联系将使未来的肿瘤学家能够获得个性化的治疗方案。放疗是首个获得美国国家健康与医疗优化研究所(NICE)批准的基于人工智能的建议。目前由临床医生承担的许多工作都由人工智能系统接管,如量纲、计划和质量保证等,因此有机会彻底改变工作流程。教育和培训对于理解人工智能流程和输入至关重要。但是,临床医生必须有信心查询人工智能生成的信息,并将人工智能生成的治疗计划传达给患者。
{"title":"The Use of Artificial Intelligence Technologies in Cancer Care","authors":"P.J. Hoskin","doi":"10.1016/j.clon.2024.09.003","DOIUrl":"10.1016/j.clon.2024.09.003","url":null,"abstract":"<div><div>Artificial intelligence (AI) is already an essential tool in the handling of large data sets in epidemiology and basic research.</div><div>Significant contributions to radiological diagnosis are emerging alongside increasing use of digital pathology. The future lies in integrating this information together with clinical data relevant to each individual patient. Linkage with clinical protocols will enable personalized management options to be presented to the oncologist of the future.</div><div>Radiotherapy has the distinction of being the first to have a National Institute for Health and Care Excellence (NICE)-approved AI-based recommendation. There is the opportunity to revolutionize the workflow with many tasks currently undertaken by clinicians taken over by AI-based systems for volume outlining, planning, and quality assurance.</div><div>Education and training will be essential to understand the AI processes and inputs. Clinicians will however have to feel confident interrogating the AI-derived information and in communicating AI-derived treatment plans to patients.</div></div>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"38 ","pages":"Article 103644"},"PeriodicalIF":3.2,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142379183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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Clinical oncology
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