An urgent call to raise the bar in oncology

Schnog, John‐John B.; Samson, Michael; Gans, Rijk O. B.; Duits, Ashley J.

doi:10.1038/s41416-021-01495-7

Cited by 43 publications

(45 citation statements)

References 134 publications

(174 reference statements)

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“… 63 , 64 Because regulatory approval standards represent not only the current thinking of regulators, but also guide the vision of what a “good drug” should be, 65 our findings highlight the need for more attention to the clinical meaningfulness—in terms of type and magnitude of benefit 66 —of newly authorized and investigational cancer therapies in China. 67 , 68 …”

Section: Discussionmentioning

confidence: 99%

Overall Survival Benefits of Cancer Drugs Approved in China From 2005 to 2020

et al. 2022

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Key Points Question What is the overall survival benefit of cancer drugs approved in China between 2005 and 2020? Findings In this mixed-methods study comprising a systematic review and cross-sectional analysis of 78 cancer drugs for 141 indications, 68 new cancer drug indications approved by Chinese authorities between 2005 and 2020 had documented evidence of overall survival benefit, and 34 did not prolong life. Meaning Given regulatory reforms in recent years, these findings highlight the need to routinely monitor the clinical benefits of new cancer therapies in China.

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Section: Discussionmentioning

confidence: 99%

Overall Survival Benefits of Cancer Drugs Approved in China From 2005 to 2020

et al. 2022

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“…Given that very short survival often is synonymous to active treatment in the last 30 days of life, oncologists can opt for palliative and supportive care rather than brain-directed therapy [ 6 ]. Supposing they choose brain-directed therapy, the challenge is to navigate a complex scenario of low-value care, potential overtreatment and futile, but costly procedures [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

30-day mortality in patients treated for brain metastases: extracranial causes dominate

et al. 2022

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Background Established prognostic models, such as the diagnosis-specific graded prognostic assessment, were not designed to specifically address very short survival. Therefore, a brain metastases-specific 30-day mortality model may be relevant. We hypothesized that in-depth evaluation of a carefully defined cohort with short survival, arbitrarily defined as a maximum of 3 months, may provide signals and insights, which facilitate the development of a 30-day mortality model. Methods Retrospective analysis (2011–2021) of patients treated for brain metastases with different approaches. Risk factors for 30-day mortality from radiosurgery or other primary treatment were evaluated. Results The cause of death was unrelated to brain metastases in 61%. Treatment-related death (grade 5 toxicity) did not occur. Completely unexpected death was not observed, e.g. accident, suicide or sudden cardiac death. Logistic regression analysis showed 9 factors associated with 30-day mortality (each assigned 3–6 points) and a point sum was calculated for each patient. The point sum ranged from 0 (no risk factors for death within 30 days present) to 30. The results can be grouped into 3 or 4 risk categories. Eighty-three percent of patients in the highest risk group (> 16 points) died within 30 days, and none survived for more than 2 months. However, many cases of 30-day mortality (more than half) occurred in intermediate risk categories. Conclusion Extracranial tumor progression was the prevailing cause of 30-day mortality and few, if any deaths could be considered relatively unexpected when looking at the complete oncological picture. We were able to develop a multifactorial prediction model. However, the model’s performance was not fully satisfactory and it is not routinely applicable at this point in time, because external validation is needed to confirm our hypothesis-generating findings.

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“…AI, however, may tip this balance to the side of benefit as it has the potential to improve cancer grading and reproducibility, thereby improving patient treatment and potentially outcome, while lowering costs. This is specifically promising, as the current trend in oncology seems to be that improving patient care may only be realized at higher costs [21].…”

Section: Developing Ai-implementation Studiesmentioning

confidence: 99%

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

et al. 2022

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Building on a growing number of pathology labs having a full digital infrastructure for pathology diagnostics, there is a growing interest in implementing artificial intelligence (AI) algorithms for diagnostic purposes. This article provides an overview of the current status of the digital pathology infrastructure at the University Medical Center Utrecht and our roadmap for implementing AI algorithms in the next few years.

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An urgent call to raise the bar in oncology

Cited by 43 publications

References 134 publications

Overall Survival Benefits of Cancer Drugs Approved in China From 2005 to 2020

Overall Survival Benefits of Cancer Drugs Approved in China From 2005 to 2020

30-day mortality in patients treated for brain metastases: extracranial causes dominate

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

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