Comparing Hypofractionated With Conventional Fractionated Radiotherapy After Breast-Conserving Surgery for Early Breast Cancer: A Meta-Analysis of Randomized Controlled Trials

Background

The purpose of this meta-analysis was to compare the safety and efficacy between hypofractionated and conventional fractionation radiotherapy in patients with early-stage breast cancer after breast-conserving surgery.

Methods

We conducted a comprehensive search of PubMed, Embase, Web of Science, and the Cochrane Library to identify relevant randomized controlled trials (RCTs) published before February 2021. At the same time, the hazard ratio (HR), risk ratio (RR), and 95% confidence interval (CI) were calculated to evaluate local recurrence (LR), relapse-free survival (RFS), overall survival (OS), adverse events, and cosmetic outcomes.

Results

A total of 14 articles were included in this meta-analysis. Four thousand eight hundred and sixty-nine patients were randomly assigned to the control group to receive conventional radiotherapy (CFRT); 6,072 patients were randomly assigned to the experimental group and treated with hypofractionated radiotherapy (HFRT). The results showed that there was no statistical difference between HFRT and CFRT in LR (HR = 0.99, 95%CI = 0.97-1.02, p = 0.476), RFS (HR = 0.99, 95%CI = 0.97-1.02, p = 0.485), OS (HR = 1.00, 95%CI = 0.97-1.03, p = 0.879), and cosmetic outcomes (RR = 1.03, 95%CI = 0.95-1.12, p = 0.53). In addition, HFRT showed fewer severe adverse reactions such as acute skin toxicity, induration, breast atrophy, and pain.

Conclusion

Our results suggest that there is no statistical difference between HFRT and CFRT in terms of LR, RFS, OS, and cosmetic outcomes. HFRT reduces the risk of developing toxicity reactions compared to CFRT. HFRT may be a better option for patients with early breast cancer after breast-conserving surgery.

Development of generalized time-dependent TCP model and the investigation of the effect of repopulation and weekend breaks in fractionated external beam therapy

We developed a tumor control probability (TCP) model that incorporates variable time intervals between fractions and a kick-off time (T_k) for radiation-induced accelerated tumor proliferation. The resulting Lee-Rosen model, TCP_LR, was used to compute TCPs for treatment courses with and without weekend treatment for tumors with different proliferation rates - slow (prostate), moderate (breast), and rapid (head and neck). TCPs were computed using ideal uniform dose distributions and actual patient plans. The doses for the uniform plans were the mean doses for the prostate and breast cases and the minimum tumor dose for the head and neck case. The TCP_LR model predictions agreed with expectations that TCP increases with increasing T_k in all cases. For standard fractionation, as T_k increased from 0 to 4 weeks, TCP increased for the patient distributions by 74.7% for the head and neck cancer, by 6.2% for the breast cancer, and by 2.4% for the prostate cancers. For the uniform dose distributions, the increases were 79.2%, 5.7%, and 2.3%, respectively. TCP increased as the number of weekend breaks decreased. The effect of weekend breaks decreased as the tumor proliferation rate decreased. For the head and neck tumor, notable decreases in TCP of 6.0% (uniform dose distribution) and 6.8% (actual plan dose distribution) were observed with Friday starts compared to Monday starts for the standard 5 fx/wk schedule (T_k = 4 wk). The 7 fx/wk schedule produced increases in TCP of 17.0% and 20.5% for the uniform and patient dose distributions, respectively, compared to the standard schedule. For the breast cancer, starting the 5 fx/wk schedule on Friday decreased the TCP by 0.2% (T_k = 4 wk) compared to a Monday start. The 7 fx/wk schedule produced increases of 0.3% and 0.4% in TCP compared to the standard schedule for the uniform and patient dose distributions, respectively (T_k = 4 wk). For the prostate cancer, the change in TCP for 5 fx/wk schedules starting on different days was 0.1%. The 7 fx/wk schedule increased TCP by 0.8% compared to the standard schedule (T_k = 4 wk). TCP values for the uniform dose distributions for the standard schedule (T_k = 4 wk) agreed with the TCP values for the actual dose distributions within 4.5% for the head and neck tumor and within 0.2% for the breast and prostate tumors. This good agreement suggests that the doses chosen for the uniform dose distributions were good approximations to the clinical doses. The results for head and neck tumors support, in part, the current practice of hyperfractionated/accelerated radiotherapy. They also suggest that shortening the overall treatment time for conventional fractions by eliminating weekend breaks might be beneficial. The predicted effect on TCP of the various schedules studied was insignificant for prostate and breast tumors, suggesting that a weekend treatment might not be necessary for patients starting radiotherapy on a Friday. There is significant uncertainty in the values of the model parameters chosen for these calculations, and no consideration was given to the potential effects of these various schedules on normal tissues.

Test the Effectiveness of Quantitative Linear-Quadratic-Based (qLQB) Model on Evaluating Irradiation-Induced Liver Injury (ILI) Against Normal Tissue Complication Probability (NTCP)

Objectives:

To test the effectiveness of quantitative linear-quadratic-based (qLQB) model on evaluating irradiation-induced liver injury (ILI) and establish the relation between the damaged ratio/percent (DRP) in qLQB model and normal tissue complication probility (NTCP).

Materials and Methods:

We established the qLQB model to calculate the ratio/percent (RP) between damaged cell/functional subunit (FSU) and entire cell/FSU of liver for radiation dose response, tested the qLQB against the Lyman-Kutcher-Burman (LKB) model, and established relation between the RP and NTCP through analyzing the dose of 32 patients with cancer of abdominal cavity who were treated with radiation therapy at our department. Based on varied α/β and varied parameters for NTCP, we put the calculated results into varied arrays for the next analysis. We named the 2 groups of RPs: RP1 (α/β = 3.0, α = 0.03) and RP2 (α/β = 8.0, α = 0.26), and named the 2 groups of NTCPs: NTCP1 (n = 0.32, m = 0.15, TD50(1) = 4000 cGy) and NTCP2 (n = 1.10, m = 0.28, TD50(1) = 4050 cGy).

Results:

Spearman correlation analysis was used to analyze the correlations among the groups, the results were as follows: RP1 vs NTCP1, rs = 0.83827, p < 0.0001; RP1 vs NTCP2, rs = 0.83827, p < 0.0001; RP2 vs NTCP2, rs = 0.79289, p < 0.0001; and RP2 vs NTCP1, rs = 0.79289, p < 0.0001.

Conclusions:

There is a significant correlation between RP value and NTCP for evaluating ILI, and there is no difference between qLQB model and LKB model on evaluating ILI.

Applications of Nonlinear Programming to the Optimization of Fractionated Protocols in Cancer Radiotherapy

The present work of review collects and evidences the main results of our previous papers on the optimization of fractionated radiotherapy protocols. The problem under investigation is presented here in a unitary framework as a nonlinear programming application that aims to determine the optimal schemes of dose fractionation commonly used in external beam radiotherapy. The radiation responses of tumor and normal tissues are described by means of the linear quadratic model. We formulate a nonlinear, non-convex optimization problem including two quadratic constraints to limit the collateral normal tissue damages and linear box constraints on the fractional dose sizes. The general problem is decomposed into two subproblems: (1) analytical determination of the optimal fraction dose sizes as a function of the model parameters for arbitrarily fixed treatment lengths; and (2) numerical determination of the optimal fraction number, and of the optimal treatment time, in different parameter settings. After establishing the boundedness of the optimal number of fractions, we investigate by numerical simulation the optimal solution behavior for experimentally meaningful parameter ranges, recognizing the crucial role of some parameters, such as the radiosensitivity ratio, in determining the optimality of hypo- or equi-fractionated treatments. Our results agree with findings of the theoretical and clinical literature.

A feasibility study of spatiotemporally integrated radiotherapy using the LQ model

This paper investigates the feasibility of spatiotemporally modulated radiotherapy (STMRT)-integrated model with explicit constraints on the tumor dose heterogeneity. In particular, we demonstrate the effect of the tumor dose heterogeneity on the tumor biologically effective dose (BED) achievable and optimal fractionation. We propose an STMRT model that simultaneously optimizes the dose distributions and fractionation schedule for each individual case with the maximum and minimum constraints on the tumor BED to explicitly control the level of tumor dose heterogeneity. Sixteen thoracic phantom cases were planned using (1) STMRT and (2) standard fractionation (60 Gy in 30 fractions fixed) IMRT. Constraints on the organs-at-risk (OAR) BED were identical for both plans. BEDs were calculated using the [Formula: see text] ratio of 10 Gy for the tumor and 3 Gy for all OARs. The maximum tumor BED for STMRT plans was constrained to be less than 100%-150% of the maximum tumor BED resulted from the standard fractionation plans. The mean tumor BED from STMRT plans was up to 110.7%, 128.3%, 135.0% and 148.0% of that from the standard fractionation plans when the maximum tumor BED was constrained to be less than 100%, 120%, 130% and 150% of the maximum BED achieved using the standard plans. The optimal number of fractions varied widely for different phantom geometries for the same radiobiological parameter values. The increase in the tumor BED and the range of optimal fractionation was larger with a larger tumor dose heterogeneity allowed. The results have shown the feasibility of personalizing fractionation schedule using an STMRT integrated model to deliver a maximum feasible BED to the tumor for a fixed OAR BED. The potential increase in the tumor BED was positively correlated to the tumor dose heterogeneity allowed.