Department of Radiation Oncology, Weill Cornell Medicine, New York, New York.
Weill Cornell Medical College, New York, New York.
JAMA Netw Open. 2021 Jan 4;4(1):e2034065. doi: 10.1001/jamanetworkopen.2020.34065.
The coronavirus disease 2019 (COVID-19) pandemic has led to treatment delays for many patients with cancer. While published guidelines provide suggestions on which cases are appropriate for treatment delay, there are no good quantitative estimates on the association of delays with tumor control or risk of new metastases.
To develop a simplified mathematical model of tumor growth, control, and new metastases for cancers with varying doubling times and metastatic potential and to estimate tumor control probability (TCP) and metastases risk as a function of treatment delay interval.
DESIGN, SETTING, AND PARTICIPANTS: This decision analytical model describes a quantitative model for 3 tumors (ie, head and neck, colorectal, and non-small cell lung cancers). Using accepted ranges of tumor doubling times and metastatic development from the clinical literature from 2001 to 2020, estimates of tumor growth, TCP, and new metastases were analyzed for various treatment delay intervals.
Risk estimates for potential decreases in local TCP and increases in new metastases with each interval of treatment delay.
For fast-growing head and neck tumors with a 2-month treatment delay, there was an estimated 4.8% (95% CI, 3.4%-6.4%) increase in local tumor control risk and a 0.49% (0.47%-0.51%) increase in new distal metastases risk. A 6-month delay was associated with an estimated 21.3% (13.4-30.4) increase in local tumor control risk and a 6.0% (5.2-6.8) increase in distal metastases risk. For intermediate-growing colorectal tumors, there was a 2.1% (0.7%-3.5%) increase in local tumor control risk and a 2.7% (2.6%-2.8%) increase in distal metastases risk at 2 months and a 7.6% (2.2%-14.2%) increase in local tumor control risk and a 24.7% (21.9%-27.8%) increase in distal metastases risk at 6 months. For slower-growing lung tumors, there was a 1.2% (0.0%-2.8%) increase in local tumor control risk and a 0.19% (0.18%-0.20%) increase in distal metastases risk at 2 months, and a 4.3% (0.0%-10.6%) increase in local tumor control risk and a 1.9% (1.6%-2.2%) increase in distal metastases risk at 6 months.
This study proposed a model to quantify the association of treatment delays with local tumor control and risk of new metastases. The detrimental associations were greatest for tumors with faster rates of proliferation and metastasis. The associations were smaller, but still substantial, for slower-growing tumors.
2019 年冠状病毒病（COVID-19）大流行导致许多癌症患者的治疗延误。虽然已发表的指南就哪些病例适合治疗延迟提供了建议，但对于延迟与肿瘤控制或新发转移风险之间的关系，尚无良好的定量估计。
为具有不同倍增时间和转移潜能的癌症建立一个肿瘤生长、控制和新发转移的简化数学模型，并估计肿瘤控制概率（TCP）和转移风险作为治疗延迟间隔的函数。
设计、地点和参与者：本决策分析模型描述了 3 种肿瘤（即头颈部、结直肠和非小细胞肺癌）的定量模型。使用 2001 年至 2020 年临床文献中接受的肿瘤倍增时间和转移发展范围，分析了各种治疗延迟间隔下的肿瘤生长、TCP 和新发转移的估计值。
治疗延迟每间隔一段时间，局部 TCP 潜在下降和新转移增加的风险估计值。
对于 2 个月治疗延迟的快速生长的头颈部肿瘤，局部肿瘤控制风险估计增加 4.8%（95%CI，3.4%-6.4%），新远处转移风险增加 0.49%（0.47%-0.51%）。6 个月的延迟与局部肿瘤控制风险估计增加 21.3%（13.4-30.4）和远处转移风险增加 6.0%（5.2-6.8）相关。对于中等生长的结直肠肿瘤，2 个月时局部肿瘤控制风险增加 2.1%（0.7%-3.5%），远处转移风险增加 2.7%（2.6%-2.8%）；6 个月时局部肿瘤控制风险增加 7.6%（2.2%-14.2%），远处转移风险增加 24.7%（21.9%-27.8%）。对于生长较慢的肺癌肿瘤，2 个月时局部肿瘤控制风险增加 1.2%（0.0%-2.8%），远处转移风险增加 0.19%（0.18%-0.20%）；6 个月时局部肿瘤控制风险增加 4.3%（0.0%-10.6%），远处转移风险增加 1.9%（1.6%-2.2%）。
本研究提出了一种模型来量化治疗延迟与局部肿瘤控制和新发转移风险之间的关联。增殖和转移速度较快的肿瘤相关性最大。生长较慢的肿瘤相关性较小，但仍然较大。
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