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从癌症患者无法治愈之时起,对其症状及心理社会困扰进行筛查与多维评估。

Screening versus multidimensional assessment of symptoms and psychosocial distress in cancer patients from the time of incurability.

作者信息

Solar Stefanie, Wieditz Johannes, Lordick Florian, Mehnert-Theuerkauf Anja, Oechsle Karin, van Oorschot Birgitt, Thomas Michael, Asendorf Thomas, Nauck Friedemann, Alt-Epping Bernd

机构信息

Department of Palliative Medicine, University Medical Center Göttingen, Göttingen, Germany.

Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany.

出版信息

Front Oncol. 2023 Jan 26;13:1002499. doi: 10.3389/fonc.2023.1002499. eCollection 2023.

DOI:10.3389/fonc.2023.1002499
PMID:36776341
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9908949/
Abstract

OBJECTIVE

Previous symptom prevalence studies show a diverse spectrum of symptoms and a large diversity in symptom intensities in patients being just diagnosed as having incurable cancer. It is unclear, how physical symptoms and psychosocial burden should be recorded in order to determine the variable need for palliative care and further support. Therefore, we compared two different strategies for detecting physical symptoms and psychosocial burden of patients with newly diagnosed incurable cancer and their effects on the further course of the disease.

METHODS

SCREBEL is a controlled, randomized, non-blinded, longitudinal study of the research network of the Palliative Medicine Working Group (APM) of the German Cancer Society (DKG). We compared: a less complex repeated brief for symptoms and burden in patients using the NCCN Distress Thermometer and IPOS questionnaire versus a multidimensional comprehensive using the FACT-G and their entity-specific questionnaires, the PHQ4 scales, SCNS-34-SF, IPOS and NCCN Distress Thermometer. The primary study endpoint was quality of life (QoL), measured using FACT-G, after six months. Secondary study endpoints were QoL by using evaluation of secondary scores (NCCN DT, IPOS, PHQ4, SCNS-SF-34G) at time 6 months, the number of hospital days, the utilization of palliative care, emergency services, and psychosocial care structures. To assess effects and differences, multiple linear regression models were fitted and survival analyses were conducted.

RESULTS

504 patients were included in the study. 262 patients were lost to follow-up, including 155 fatalities. There were no significant differences between the low-threshold approach and a comprehensive with respect to symptoms and other aspects of QoL. Using the IPOS, we were able to measure an improvement in the quality of life in the low-threshold arm by a decrease of 0.67 points (95%-CI: 0.34 to 0.99) every 30 days. (p<0.001). Data on the involvement of emergency facilities and on supportive services were insufficient for analysis.

CONCLUSION

A comprehensive, multidimensional did not significantly differ from brief in preserving several dimensions of quality of life. These findings may positively influence the implementation of structured low-threshold screening programs for supportive and palliative needs in DKG certified cancer centers.DRKS -No. DRKS00017774 https://drks.de/search/de/trial/DRKS00017774.

摘要

目的

既往症状患病率研究表明,刚被诊断为患有不治之症癌症的患者症状谱多样,症状强度差异很大。目前尚不清楚应如何记录身体症状和心理社会负担,以确定对姑息治疗和进一步支持的不同需求。因此,我们比较了两种不同的策略,用于检测新诊断为不治之症癌症患者的身体症状和心理社会负担,以及它们对疾病后续进程的影响。

方法

SCREBEL是德国癌症协会(DKG)姑息医学工作组(APM)研究网络开展的一项对照、随机、非盲纵向研究。我们比较了:一种不太复杂的重复简短评估,使用美国国立综合癌症网络(NCCN)苦恼温度计和国际患者结局量表(IPOS)问卷评估患者的症状和负担,与一种多维综合评估,使用癌症治疗功能评估量表(FACT-G)及其特定实体问卷、患者健康问卷-4量表(PHQ4)、简明症状量表-34简表(SCNS-34-SF)、IPOS和NCCN苦恼温度计。主要研究终点是6个月后使用FACT-G测量的生活质量(QoL)。次要研究终点是6个月时使用次要评分(NCCN DT、IPOS、PHQ4、SCNS-SF-34G)评估的QoL、住院天数、姑息治疗、急诊服务和心理社会护理结构的使用情况。为评估效果和差异,拟合了多元线性回归模型并进行了生存分析。

结果

504例患者纳入研究。262例患者失访,其中155例死亡。低门槛评估方法与综合评估方法在症状和QoL的其他方面没有显著差异。使用IPOS,我们能够测量低门槛评估组中生活质量的改善,每30天下降0.67分(95%置信区间:0.34至0.99)。(p<(此处原文缺失比较对象)0.001)。关于急诊设施参与情况和支持性服务的数据不足以进行分析。

结论

在维持生活质量的几个维度方面,全面的多维评估与简短评估没有显著差异。这些发现可能会对德国癌症协会认证的癌症中心实施针对支持性和姑息性需求的结构化低门槛筛查项目产生积极影响。德国临床试验注册中心编号:DRKS00017774 网址:https://drks.de/search/de/trial/DRKS00017774 。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/80d5e3c21d55/fonc-13-1002499-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/46795907caa7/fonc-13-1002499-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/f93c94c2f617/fonc-13-1002499-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/b9f21d329794/fonc-13-1002499-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/80d5e3c21d55/fonc-13-1002499-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/46795907caa7/fonc-13-1002499-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/f93c94c2f617/fonc-13-1002499-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/b9f21d329794/fonc-13-1002499-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/40ed/9908949/80d5e3c21d55/fonc-13-1002499-g004.jpg

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