# Radiation doses to the breast and predicted breast cancer risk among patients treated for Hodgkin lymphoma with modern radiotherapy

Sander Roberti, Nicola S Russell, Ruth M Pfeiffer, Inge M Krul, Florent de Vathaire, Cristina Veres, Ibrahima Diallo, Cécile P M Janus, Joan Penninkhof, René Vernhout, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Sander Roberti, Nicola S Russell, Ruth M Pfeiffer, Inge M Krul, Florent de Vathaire, et al. Radiation doses to the breast and predicted breast cancer risk among patients treated for Hodgkin lymphoma with modern radiotherapy. International Journal of Radiation Oncology, Biology, Physics, 2025, 10.1016/j.ijrobp.2024.12.016. hal-04953950

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<figure><img src="image_2.png" /></figure>
CLINICAL INVESTIGATION

# Radiation Doses to the Breast and Predicted Breast Cancer Risk Among Patients Treated for Hodgkin Lymphoma With Modern Radiation Therapy

Sander Roberti, PhD,<sup>a,b</sup> Nicola S. Russell, PhD,<sup>c</sup> Ruth M. Pfeiffer, PhD,<sup>b</sup> Inge M. Krul, PhD,<sup>a</sup>

Florent de Vathaire, PhD,<sup>d,e,f</sup> Cristina Veres, MSc,<sup>f,g,h</sup> Ibrahima Diallo, PhD,<sup>f,g,h</sup> Cécile P.M. Janus, MD,<sup>i</sup>

Joan Penninkhof, PhD,<sup>j</sup> René Vernhout, MSc,<sup>j</sup> André Buchali, MD,<sup>j</sup> Eyck Blank, PhD,<sup>j</sup>

Flora E. van Leeuwen, PhD,<sup>a</sup> and Michael Hauptmann, PhD<sup>k</sup>

<sup>a</sup>Department of Epidemiology and Biostatistics, The Netherlands Cancer Institute, Amsterdam, The Netherlands; <sup>b</sup>Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland; <sup>c</sup>Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, the Netherlands; <sup>d</sup>Radiation Epidemiology Team, Center for Research in Epidemiology and Population Health, INSERM U1018, Villejuif, France; <sup>e</sup>Research Department, Gustave Roussy, Villejuif, France; <sup>f</sup>University Paris Saclay, Villejuif, France; <sup>g</sup>Molecular Radiation Therapy and Therapeutic Innovation, INSERM U1030, Villejuif, France; <sup>h</sup>Radiation Oncology Department, Gustave Roussy, Villejuif, France; <sup>j</sup>Department of Radiation Oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands; <sup>k</sup>Department of Radiation Oncology, University Hospital Ruppin-Brandenburg, Brandenburg Medical School Theodor Fontane, Neuruppin, Germany; and <sup>l</sup>Institute of Biostatistics and Registry Research, Brandenburg Medical School Theodor Fontane, Neuruppin, Germany

Received Jul 2, 2024; Accepted for publication Dec 23, 2024

**Purpose:** To contrast breast radiation exposure from chest radiation therapy (RT) between 2006 and 2021 with those given between 1965 and 1997, and to compare breast cancer (BC) risk 25 years after treatment predicted using 2 models.

**Methods and Materials:** Radiation dose distributions to the breast from 101 chest RTs given from 2006 until 2021 for Hodgkin lymphoma (HL) or other lymphoma in 1 German and 2 Dutch hospitals were compared with doses received by 505 Dutch patients with HL treated from 1965 until 1997 and sampled into a nested case-control study, weighted to represent a cohort of patients with HL. Dose-volume histograms, mean dose, and doses to 10 breast segments were evaluated. Absolute BC risks 25 years after historic and recent treatments were estimated for low- and high-risk profiles (HL stage III versus I at age 24 in 2010, treatment-induced menopause at age 24 years versus none, first live birth at age 20 years versus nulliparous, BC family history no versus yes, no HL relapse, nonsmoking at HL diagnosis, exposed to anthracyclines and cardiotoxic RT).

**Results:** The average mean breast dose decreased from 21.4 Gy for historic to 3.0 Gy for recent treatments. The breast volume receiving ≥ 20 Gy ($V_{20}$) decreased from 48.7% to 2.2%, and the lowest dose to the highest exposed 20% of breast volume ($D_{20}$)

Corresponding author: Michael Hauptmann, PhD; E-mail: michael.hauptmann@mhb-fontane.de

Authors responsible for statistical analysis: Sander Roberti, PhD; Email: sander.roberti@nih.gov; Michael Hauptmann, PhD; Email: michael.hauptmann@mhb-fontane.de

Disclosures: The department of radiation oncology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands has ongoing research collaborations with Elekta AB, Accuray Inc, VisionRT, and Varian Medical Systems. JP presented at User Meetings, for which a speaking fee was received. This work was supported by the Dutch Cancer Society (grant number

KWF10004) and the intramural program of the National Cancer Institute, National Institutes of Health, Bethesda, Maryland.

Data Sharing Statement: The recent treatment data were transferred under data transfer agreements for the sole purpose of this study and therefore cannot be shared.

Acknowledgments—We thank Dr Kristin Schnuppe from the Center for Clinical Studies of the Brandenburg Medical School, Neuruppin, Germany, for her assistance.

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.ijrobp.2024.12.016.
from 39.0 Gy to 2.8 Gy. Most metrics decreased from 2006 to 2021. Using quadrant-specific doses, median absolute BC risk 25 years after treatment decreased from 21.0% to 6.9% for historic versus recent treatments for a high-risk patient and from 3.1% to 0.9% for a low-risk patient, respectively. Using mean dose, median absolute BC risks decreased from 20.3% to 6.0% and from 3.1% to 0.9% for the high- and low-risk patients, respectively.

**Conclusions:** Modern RT treatments expose the breast to lower radiation doses and irradiated volumes than those used before 2000. BC risk predictions using the mean breast dose were slightly lower than predictions using quadrant-specific doses. © 2025 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

## Introduction

Female patients who received chest radiation therapy (RT) for Hodgkin lymphoma (HL) or other childhood malignancies have a substantially increased risk of breast cancer (BC) decades later.<sup>1,2</sup> BC risk predictions for such patients often use data from patients treated decades ago with long-term follow-up to observe the late effects.<sup>3-5</sup> Such predictions may not apply to patients treated more recently, because modern RT uses smaller target volumes and lower prescribed radiation doses compared with previous decades.<sup>6-8</sup> The reduction in prescribed doses and the shift from extended-field treatments, such as mantle field, to involved field and involved site treatments substantially reduced breast exposure.<sup>8</sup> At the same time, treatment techniques evolved from conventional 2- to 3-dimensional conformal RT to intensity modulated RT, allowing for better dose conformity, ie, treatments matching the shape of the tumor with lower RT exposure to healthy tissue. Usually, organs at risk, such as the heart, receive lower doses, but at the expense of a larger volume of other tissue (such as the breast) receiving doses around 5 Gy.<sup>6,9</sup> Thus, modern treatments produce different dose distributions than techniques used in the past.

We recently developed BC risk prediction models that incorporate radiation doses to quadrants of the breast from patients with HL treated from 1963 until 1998. The goal was to obtain accurate BC risk predictions for women treated with contemporary RT by incorporating detailed BC dose distributions, despite the different radiation doses and volumes of previously treated patients with long follow-ups, whose data were used to develop the models.<sup>10,11</sup> The models were validated in patients with HL from the Childhood Cancer Survivor Study, treated between 1970 and 1986.<sup>12</sup> Model validation using data from more recently treated HL survivors is not feasible because of the lack of long enough follow-up to observe treatment-related second cancer events.

Here, we used a sample of recently irradiated patients with HL and other lymphoma (2006-2021) with radiation exposure to the breast, from 2 hospitals in the Netherlands and 1 hospital in Germany, and compared their dose distributions to those from treatments of patients diagnosed with HL from 1965 until 1997. We also compared predicted absolute BC risks based on quadrant-specific breast doses with those based on mean breast doses for current radiation treatments to assess the difference between the novel quadrant-based model and the simpler mean dose model.

## Methods and Materials

### Study population

We obtained data from 130 patients with HL or other lymphoma treated in 3 hospitals in the Netherlands and Germany (The Netherlands Cancer Institute, Amsterdam [NKI]; Erasmus Medical Center, Rotterdam [EMC]; University Hospital Brandenburg-Ruppin, Neuruppin [UKRB]). Each hospital selected patients based on the following criteria: (1) female sex, (2) aged 15 years or older at the time of cancer diagnosis, (3) cancer diagnosis in 2006 or later, (4) RT treatment using any technique after computed tomography CT-based treatment planning, with the breast partly in the RT field, (5) feasible to delineate all quadrants and the central area of both breasts and to determine RT-related radiation dose to all these segments. We did not select patients who received palliative RT and excluded patients with a non-HL in the breast. Basic demographic and clinical characteristics of the primary diagnosis were collected: age at diagnosis, year of treatment, cancer topography, morphology, and sublocalization (if applicable); treatment with chemotherapy (yes/no), treatment with alkylating agents (yes/no), and treatment with procarbazine (yes/no). From the 130 selected patients, we excluded 15 patients with incomplete dosimetry or breast contours and 14 patients whose cancer was located in the breast, leaving 101 patients in the analytic data set. Institutional review board approval was obtained in each center.

### Radiation exposure

For each patient, information on radiation technique and target volumes was obtained. Total breast volume and volume of 5 segments per breast were delineated using European Society for Radiotherapy and Oncology guidelines.<sup>13</sup> First, the central area was defined as a cylinder with a diameter of 2 cm around the nipple in the dorsal direction. The upper outer quadrant, upper inner quadrant, lower outer quadrant, and lower inner quadrant were then defined using the 12, 3, 6, and 9 o'clock directions as borders. Treatment planning systems were used at each center to extract the overall dose-volume histogram (DVH) for both breasts and to obtain the mean dose to the total breast volume ("mean breast dose") and the mean dose to each of the 10 segments, which we call "quadrant-specific doses" below. From the DVH, we extracted parameters $D_{10}$, $D_{20}$, and $D_{80}$.
(D<sub>x</sub> = minimum dose received by x% of the breast volume with the highest dose), V<sub>5</sub>, V<sub>20</sub>, V<sub>35</sub>, and V<sub>40</sub> (V<sub>y</sub> = % of breast volume receiving at least y Gy).<sup>14</sup> To assess dose concentration, we determined the median dose to the breast volume receiving at least 5 Gy, which we denoted using D<sub>50|5</sub>. For patients without any breast volume exposed to 5 Gy or more, ie, V<sub>5</sub> = 0, we defined D<sub>50|5</sub> = 5 Gy, as the smallest possible value for a woman with any part of the breast exposed to at least 5 Gy.

## Historic treatment data

The historic treatment data came from the BRIGHT study,<sup>15</sup> a nested BC case-control study sampled from a cohort of 1194 female 5-year HL survivors diagnosed at age 11-40 years in 1965-2000 in 1 of 6 Dutch hospitals. In the current study, radiation dose distributions in the breasts were reconstructed for the 151 BC cases and 354 controls who were exposed to RT from 1965 until 1997, by approximating each treatment using a combination of field types from a catalog of 43 commonly occurring treatments in the relevant treatment era.<sup>16</sup>

## Statistical analysis

To approximate the distribution of dose metrics and field types in the population of general historic HL patients, we weighted patients exposed to RT from the nested case-control study back to represent the 1028 survivors treated with RT among 1194 women in the cohort. We used the inverse of the probability of inclusion weights (“sampling weights”) stratified using the matching factors (age and calendar year of HL diagnosis) as described in Roberti et al.<sup>10</sup> Recently irradiated patients formed a separate population and were all sampled and assigned a weight of 1. We plotted the values of each dose metric by calendar time and added separate linear fits for historically and recently treated patients. Likelihood ratio trend tests for the year of treatment were performed for dose metrics over time, both in a linear (continuous characteristics) or logistic (binary characteristics) regression model.

Absolute BC risks were estimated using models in Roberti et al<sup>10</sup> based on quadrant-specific doses (model L1) and overall mean breast dose (model P1), with baseline risks estimated from the Dutch HL survivors cohort. In both models, the radiation-related relative risk (RR) was modeled as RR = 1 + β dose, where β is the linear excess relative risk per Gy. The mean dose model uses the overall mean dose to the breasts, and the quadrant-specific model uses doses to 10 breast quadrants (including the central areas on either side). For every dose distribution, we computed RR = 1 + βd<sub>mean</sub> (mean dose model) with β = 0.26, or RR = Σ<sub>k=L,R</sub> Σ<sub>l=1</sub><sup>5</sup> exp(α<sub>1</sub>)(1 + βd<sub>k,l</sub>) (quadrant-specific model)

with β = 0.14, d<sub>k,l</sub> the dose to breast laterality k (L = left and R = right breast), quadrant l (central, upper outer

quadrant, upper inner quadrant, lower outer quadrant, lower inner quadrant), and α<sub>1</sub> modeling the heterogeneity in baseline risk between breast quadrants. Assuming symmetry of baseline risk, exp(α<sub>1</sub>) is the proportion of baseline risk for quadrant l, ie, Σ<sub>L,R</sub> Σ<sub>l=1</sub><sup>5</sup> exp(α<sub>1</sub>) = 2Σ<sub>l=1</sub><sup>5</sup> exp(α<sub>1</sub>) = 1. Other predictors were first-degree family history, menopausal status, parity and age at first live birth, and age at and year of HL diagnosis. Menopausal status, parity, and age at first live birth were determined 5 years after HL diagnosis. Attained age was used as the time scale. The competing risk model (death or non-BC second cancer diagnosis) included stage of HL, year of HL diagnosis, treatment with anthracyclines (yes/no), cardiotoxic RT (yes/no, ie, RT exposing the heart), HL relapse within 5 years (yes/no), recent smoking at HL diagnosis (yes/no), and time since HL diagnosis.

We combined the historic and recent dose distributions observed in the data with hypothetical profiles for the non-radiation predictors. One profile was considered low BC risk (diagnosed with stage III HL at age 24 years in 2010, treatment-induced menopause at age 24 years, first live birth at age 20 years, and no family history of BC), and the other one high BC risk (diagnosed with stage I HL at age 24 years in 2010, not menopausal, nulliparous, and family history of BC). Both patients were assumed to have no HL relapse within 5 years, to have been exposed to anthracyclines and cardiotoxic RT, and to not have smoked at HL diagnosis. The year of treatment was set to 2000, the end of follow-up for the HL survivor cohort, to avoid extrapolation for the prediction of competing events. We stress that, except for the radiation exposure distribution, no information on the patients in our study was used in assessing the impact of dose on BC risk in the analyses described next.

For both profiles, we estimated absolute risks of BC 25 years after treatment, ie, for 20 years starting at 5 years after HL diagnosis, for all dose distributions of the 101 recently irradiated patients and of the 505 historic patients using the mean dose model and the quadrant-specific model. Predicted risks for the recently treated patients were compared between models using a scatter plot. Distributions of the risk difference are shown as histograms. Additional profiles are given in Table E1. Analyses were implemented using R version 4.1.1, and *P* values < .05 were considered statistically significant.

## Results

Patients treated between 2006 and 2021 were aged 19 to 82 years at diagnosis (Table 1), and most were diagnosed with HL (59.4%). The historic patients with HL treated between 1965 and 1997 (BRIGHT study) were diagnosed at ages 11 to 41 years. Radiation doses received by each breast quadrant were substantially smaller for the recently irradiated patients than for the historic patients (all *P*-trend < .001). For example, the median upper outer quadrant dose, averaged over both breasts, was 34.5 Gy among
<table><caption>**Table 1** Characteristics of the study population</caption><thead><tr><th rowspan="2">Characteristic</th><th rowspan="2">Historically treated patients<br>BRIGHT* (n = 505)</th><th colspan="4">Recently treated patients</th><th rowspan="2">P-trend†</th></tr><tr><th>EMC (n = 59)</th><th>NKI (n = 21)</th><th>UKRB (n = 21)</th><th>Total (n = 101)</th></tr></thead><tbody><tr><td>Primary diagnosis<br>(N, %)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>HL</td><td>505 (100%)</td><td>43 (72.9%)</td><td>11 (52.4%)</td><td>6 (28.6%)</td><td>60 (59.4%)</td><td>-</td></tr><tr><td>Other lymphoma</td><td>0 (0%)</td><td>16 (27.1%)</td><td>10 (47.6%)</td><td>15 (71.4%)</td><td>41 (40.6%)</td><td>-</td></tr><tr><td>Year of treatment<br>(range)</td><td>1965-1997</td><td>2013-2020</td><td>2007-2020</td><td>2006-2021</td><td>2006-2021</td><td>-</td></tr><tr><td>Age at diagnosis (y;<br>median, range)</td><td>23.6 (11.1-41.2)</td><td>32.0 (19.0-81.0)</td><td>52.0 (23.0-80.0)</td><td>68.9 (22.9-82.3)</td><td>37.0 (19.0-82.3)</td><td>-</td></tr><tr><td>Treated with<br>chemotherapy (N, %)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>&lt; .001</td></tr><tr><td>Yes</td><td>299 (59.2%)</td><td>57 (96.6%)</td><td>14 (66.7%)</td><td>13 (61.9%)</td><td>84 (83.2%)</td><td>-</td></tr><tr><td>No</td><td>206 (40.8%)</td><td>2 (3.4%)</td><td>7 (33.3%)</td><td>8 (38.1%)</td><td>17 (16.8%)</td><td>-</td></tr><tr><td>Treated with alkylating<br>agents (N, %)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>&lt; .001</td></tr><tr><td>Yes</td><td>263 (52.1%)</td><td>57 (96.6%)</td><td>2 (9.5%)</td><td>13 (61.9%)</td><td>72 (71.3%)</td><td>-</td></tr><tr><td>No</td><td>236 (46.7%)</td><td>2 (3.4%)</td><td>19 (90.5%)</td><td>8 (38.1%)</td><td>29 (28.7%)</td><td>-</td></tr><tr><td>Unknown</td><td>6 (1.2%)</td><td>0 (0%)</td><td>0 (0%)</td><td>0 (0%)</td><td>0 (0%)</td><td>-</td></tr><tr><td>Treated with<br>procarbazine (N, %)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>.066</td></tr><tr><td>Yes</td><td>226 (44.8%)</td><td>3 (5.1%)</td><td>0 (0%)</td><td>2 (9.5%)</td><td>5 (5.0%)</td><td>-</td></tr><tr><td>No</td><td>272 (53.9%)</td><td>56 (94.9%)</td><td>21 (100%)</td><td>18 (85.7%)</td><td>95 (94.1%)</td><td>-</td></tr><tr><td>Unknown</td><td>7 (1.4%)</td><td>0 (0%)</td><td>0 (0%)</td><td>1 (4.8%)</td><td>1 (1.0%)</td><td>-</td></tr><tr><td>Breast volume (cm³;<br>median, range)</td><td>-</td><td>1069 (206-3282)</td><td>1305 (147-3940)</td><td>1112 (382-3905)</td><td>1116 (147-3940)</td><td>-</td></tr><tr><td>Mean breast dose<br>(Gy; median, range)</td><td>21.4 (0.04-43.9)</td><td>2.1 (0.1-13.3)</td><td>4.1 (0.4-12.0)</td><td>5.6 (0.1-13.7)</td><td>3.0 (0.1-13.7)</td><td>&lt; .001</td></tr><tr><td>Quadrant dose†<br>(Gy; median, range)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Central</td><td>20.2 (0.01-44.5)</td><td>0.4 (0.0-9.7)</td><td>1.4 (0.1-13.0)</td><td>2.1 (0.04-11.8)</td><td>0.7 (0.0-13.0)</td><td>&lt; .001</td></tr><tr><td>Upper inner</td><td>21.9 (0.01-43.1)</td><td>4.4 (0.2-23.5)</td><td>6.6 (0.1-21.2)</td><td>7.9 (0.1-16.2)</td><td>5.8 (0.1-23.5)</td><td>&lt; .001</td></tr><tr><td>Upper outer</td><td>34.5 (0.002-57.9)</td><td>0.9 (0.04-12.2)</td><td>6.3 (0.05-14.0)</td><td>7.9 (0.1-17.0)</td><td>2.1 (0.04-17.0)</td><td>&lt; .001</td></tr><tr><td>Lower inner</td><td>12.8 (0.01-37.1)</td><td>0.4 (0.0-11.4)</td><td>1.3 (0.1-12.7)</td><td>0.6 (0.03-14.3)</td><td>0.5 (0.0-14.3)</td><td>&lt; .001</td></tr><tr><td>Lower outer</td><td>12.3 (0.01-40.4)</td><td>0.2 (0.0-4.9)</td><td>1.3 (0.04-8.3)</td><td>0.6 (0.02-11.8)</td><td>0.4 (0.0-11.8)</td><td>&lt; .001</td></tr><tr><td>V<sub>5</sub> (%; median, range)</td><td>86.6 (0.0-100.0)</td><td>10.2 (0.0-60.5)</td><td>22.7 (0.0-78.7)</td><td>22.4 (0.0-88.1)</td><td>14.8 (0.0-88.1)</td><td>&lt; .001</td></tr><tr><td>V<sub>20</sub> (%; median, range)</td><td>48.7 (0.0-81.4)</td><td>0.9 (0.0-32.2)</td><td>5.5 (0.0-28.6)</td><td>4.0 (0.0-44.2)</td><td>2.2 (0.0-44.2)</td><td>&lt; .001</td></tr><tr><td>V<sub>35</sub> (%; median, range)</td><td>34.1 (0.0-69.9)</td><td>0.0 (0.0-5.3)</td><td>0.0 (0.0-20.9)</td><td>0.0 (0.0-2.9)</td><td>0.0 (0.0-20.9)</td><td>&lt; .001</td></tr><tr><td>V<sub>40</sub> (%; median, range)</td><td>16.6 (0.0-66.4)</td><td>0.0 (0.0-0.02)</td><td>0.0 (0.0-3.2)</td><td>0.0 (0.0-0.2)</td><td>0.0 (0.0-3.2)</td><td>&lt; .001</td></tr><tr><td>D<sub>10</sub> (Gy; median,<br>range)</td><td>40.0 (0.1-78.7)</td><td>5.2 (0.3-31.4)</td><td>10.9 (1.1-38.5)</td><td>13.5 (0.2-30.6)</td><td>9.0 (0.2-38.5)</td><td>&lt; .001</td></tr><tr><td>D<sub>20</sub> (Gy; median,<br>range)</td><td>39.0 (0.03-69.6)</td><td>1.6 (0.1-26.8)</td><td>8.4 (0.3-35.4)</td><td>8.4 (0.2-30.1)</td><td>2.8 (0.1-35.4)</td><td>&lt; .001</td></tr></tbody></table>

(Continued)
<table><caption>**Table 1 (Continued)**</caption><thead><tr><th rowspan="2">Characteristic</th><th rowspan="2">Historically treated patients<br>BRIGHT* (n = 505)</th><th colspan="4">Recently treated patients</th><th rowspan="2">P-trend†</th></tr><tr><th>EMC (n = 59)</th><th>NKI (n = 21)</th><th>UKRB (n = 21)</th><th>Total (n = 101)</th></tr></thead><tbody><tr><td>D<sub>80</sub> (Gy; median, range)</td><td>6.0 (0.0-21.9)</td><td>0.3 (0.03-1.8)</td><td>0.4 (0.04-4.8)</td><td>0.3 (0.0-6.1)</td><td>0.3 (0.0-6.1)</td><td>&lt; .001</td></tr><tr><td>D<sub>50|5</sub> (Gy; median, range)</td><td>32.2 (5.0-43.4)</td><td>12.9 (5.0-21.1)</td><td>11.9 (5.0-36.3)</td><td>10.5 (5.0-29.9)</td><td>12.4 (5.0-36.3)</td><td>&lt; .001</td></tr><tr><td>Location of breast cancer among 151 cases (N, %)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Central</td><td>21 (13.9%)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Lower inner</td><td>10 (6.6%)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Lower outer</td><td>11 (7.3%)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Upper inner</td><td>17 (11.3%)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Upper outer</td><td>63 (41.7%)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr><tr><td>Multiple segments</td><td>29 (19.2%)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td></tr></tbody></table>

Abbreviations: HL = Hodgkin lymphoma.

* Matched case-control data, ie, the numbers given in the table are not representative of a cohort of HL survivors

† Likelihood ratio test for the effect of year of treatment in a linear (continuous variables) or logistic regression (binary variables) model. Patients in BRIGHT are weighted by their sampling weight to make the weighted case-control study approximate the underlying cohort, other patients have a weight of 1. Missing values were removed before testing.

‡ Average over the left and right breast.

historic patients and 2.1 Gy among recently treated patients. The proportion of treatments including chemotherapy and alkylating agents increased significantly over time (both P-trend < .001).

Figure 1 shows the DVHs for historically and recently treated patients. Recently treated patients had smaller volumes receiving high doses, most with < 25% of the breast receiving 10 Gy or more, compared with 50% for many historic patients (Table 1). Radiation doses and volumes were smaller for recent than for historic patients (Fig. 2, Table 1, and Fig. E1). For example, recently treated patients had a smaller breast volume exposed to 5 Gy or more (P-trend <

.001, Table 1), and the median dose to the breast volume receiving at least 5 Gy (D<sub>50|5</sub>), defined as D<sub>50|5</sub> = 5 Gy for 4 historic and 5 recently treated patients with no volume receiving at least 5 Gy, also decreased over time (P-trend < .001, Table 1).

Among patients treated from 2006 until 2021, we observed decreases over time for mean dose overall and for all quadrants and the volume exposed to doses of 5 Gy or more (V<sub>5</sub>). However, the volume exposed to doses of 20 Gy or more (V<sub>20</sub>, V<sub>35</sub>, and V<sub>40</sub>) and the median dose to volumes exposed to 5 Gy or more (D<sub>50|5</sub>) did not change (Fig. E2).

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Dose-volume histograms for patients in the BRIGHT study (left panel) and recently treated patients (right panel).</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Changes in dose metrics over time. The red lines are linear fits for the historically (BRIGHT) and recently treated patients. Patients in the BRIGHT nested case-control study were weighted back to the underlying cohort of 5-year HL survivors; other patients have a weight of 1. *Abbreviations:* HL = Hodgkin lymphoma; LIQ = lower inner quadrant; LOQ = lower outer quadrant; UIQ = upper inner quadrant; UOQ = upper outer quadrant.</figcaption></figure>

The risk related to nonradiation risk factors was 7-fold higher for the hypothetical high-risk patient than for the low-risk patient (not shown). The median predicted absolute BC risk 25 years after treatment of the low-risk patient decreased from 3.1% (interquartile range [IQR], 2.4%-3.6%) for historic treatments to 0.9% (IQR, 0.8%-1.2%) for recent treatments, and from 21.0% (IQR, 16.4%-24.0%) to 6.9% (IQR, 6.0%-8.9%) for the high-risk patient (based on the quadrant-specific model).

With regard to the 2 different prediction models, for the low-risk patient, the median predicted absolute risk of BC 25 years after treatment across the 101 modern dose distributions (Fig. 1, right panel) was 0.9% (IQR, 0.8%-1.2%) based on the quadrant-specific model and 0.9% (IQR, 0.6%-1.2%) based on the mean dose model (Fig. 3, Table 2). For the high-risk patient, the corresponding numbers were 6.9% (IQR, 6.0%-8.9%) and 6.0% (IQR, 4.6%-8.2%). In the median, the quadrant-specific model predicted 15.2% (IQR, 4.1%-23.1%) and 18.2% (IQR, 7.9%-25.6%) higher risks than the mean dose model for the low- and high-risk

patient, respectively. Results were similar for additional hypothetical risk profiles given in Table E1.

Discussion

We showed that doses and irradiated volumes of the breast were lower for patients with HL and other lymphomas treated with modern techniques between 2006 and 2021 compared with historic patients treated for HL between 1963 and 1997, and predicted radiation-related BC risks were correspondingly lower. A model based on quadrant-specific breast doses predicted somewhat higher absolute BC risk 25 years after treatment than one that used mean breast dose. Postulating that the quadrant-specific model provides more accurate risk predictions because it uses more detailed information on breast exposure—an assumption that cannot be verified empirically because of the lack of follow-up for recently treated patients—using mean breast dose may slightly underestimate risk.
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Predictions of absolute risk of breast cancer 25 years after treatment for 101 modern dose distributions, based on the low- and high-risk profiles for variables other than radiation therapy and using quadrant-specific doses (quadrant-specific model) and overall mean breast dose (mean dose model). Left panel: predictions based on the mean dose model versus the quadrant-specific model. Center panel: distribution of differences between risk predicted with the quadrant-specific and mean dose model, computed as (quadrant-specific prediction – mean dose prediction). Right panel: distribution of relative differences between risk predicted with the quadrant-specific and mean dose model, computed as 100% × (quadrant-specific prediction – mean dose prediction)/quadrant-specific prediction). *Abbreviation:* pp = percentage points.</figcaption></figure>

<table><caption>**Table 2** Risk profiles</caption><thead><tr><th>Patient characteristics*</th><th>Low-risk patient</th><th>High-risk patient</th></tr></thead><tbody><tr><td>Age at HL, y</td><td>24</td><td>24</td></tr><tr><td>Year of HL</td><td>2010</td><td>2010</td></tr><tr><td>Family history of BC</td><td>No</td><td>Yes</td></tr><tr><td>Age at menopause, y</td><td>24</td><td>-</td></tr><tr><td>Age at first live birth, y</td><td>20</td><td>-</td></tr><tr><td>HL stage†</td><td>III</td><td>I</td></tr><tr><td>Cardiotoxic RT†</td><td>Yes</td><td>Yes</td></tr><tr><td>Treatment with anthracyclines†</td><td>Yes</td><td>Yes</td></tr><tr><td>HL relapse within 5 y†</td><td>No</td><td>No</td></tr><tr><td>Recent smoker at HL diagnosis†</td><td>No</td><td>No</td></tr><tr><td colspan="3">Predicted absolute BC risk 25 y after historic treatments‡</td></tr><tr><td>Quadrant-specific model (median, IQR)</td><td>3.1% (2.4%-3.6%)</td><td>21.0% (16.4%-24.0%)</td></tr><tr><td>Mean dose model (median, IQR)</td><td>3.1% (2.4%-3.9%)</td><td>20.3% (15.8%-24.9%)</td></tr><tr><td colspan="3">Predicted absolute BC risk 25 years after recent treatments§</td></tr><tr><td>Quadrant-specific model (median, IQR)</td><td>0.9% (0.8%-1.2%)</td><td>6.9% (6.0%-8.9%)</td></tr><tr><td>Mean dose model (median, IQR)</td><td>0.9% (0.6%-1.2%)</td><td>6.0% (4.6%-8.2%)</td></tr><tr><td>Relative difference between models# (median, IQR)</td><td>15.2% (4.1%-23.1%)</td><td>18.2% (7.9%-25.6%)</td></tr></tbody></table>

*Abbreviations:* BC = breast cancer; HL = Hodgkin lymphoma; IQR = interquartile range; RT = radiation therapy.

* Characteristics used for BC were age at HL, year of HL, family history of BC, age at menopause, and age at first live birth. Characteristics used for the competing event (ie, death or diagnosis with a non-BC second cancer) were HL stage, year of HL, cardiotoxic RT, treatment with anthracyclines, HL relapse within 5 years, and smoking status at HL diagnosis

† Only affects BC risk through the effect on risk of competing events. Note that factors increasing the risk of a competing event (eg, higher stage of HL) thereby decrease the absolute BC risk.

‡ Predictions based on 505 dose distributions for historic treatments.

§ Predictions based on 101 dose distributions for recent treatments.

# Relative difference between risk predictions computed as 100% × (quadrant-specific prediction – mean dose prediction)/quadrant-specific prediction.
Several studies have shown that modern radiation treatments for HL expose healthy tissue to lower doses than historic treatments and therefore reduce the risk of second cancers.⁸,¹⁷ Our study is the first to compare treatment-related exposure of the breasts of real patients treated over several decades. We are also the first to use data from recently treated patients with HL in a BC risk prediction model built on data from patients treated decades in the past. While this paper provides insight into BC risk associated with contemporary radiation treatment, it is not a validation of the model for recent patients, because long-term follow-up and therefore outcomes are lacking.

As far as we know, only 1 study has investigated exposure of the breast during current treatment for HL.¹⁸ Among 101 patients treated between 2005 and 2021 with supradiaphragmatic RT, no significant correlations with treatment years were observed for various DVH metrics. Our data show more complex patterns and suggest that the volume exposed to doses between 5 and 20 Gy decreased, while the volume exposed to higher doses (V₂₀, V₃₅, and V₄₀) did not.

Nonetheless, our study has several limitations. We attempted to obtain a representative set of patients treated with modern techniques exposing the breasts, but the number of available records of patients with HL was small because HL is rare and only a subset receives RT. We, therefore, included patients with HL with a wider range of ages at diagnosis than used for the development of the risk prediction model and patients with other types of lymphoma who received radiation exposure to the chest. However, there was no systematic difference in dose distribution parameters between HL and other types of lymphoma or between younger and older patients (Figs E2 and E3), indicating that these treatments are representative of HL treatments. Other factors that may differ between age groups or diagnoses, such as chemotherapy exposure, were not used in our analyses.

Our main goal was to compare risk prediction models for a second malignancy based on the dose to several segments of the organs at risk and the dose averaged over the entire organ. For this purpose, the breast is an ideal candidate organ. We expected higher predicted risks when using quadrant-specific doses because the upper outer quadrant, where baseline risk is higher,¹⁹ also receives generally higher doses than other quadrants (Fig. 2). However, differences between the 2 model estimates were modest. In addition, a prediction model that incorporates this spatial heterogeneity within the breast is expected to discriminate better than a model using mean breast dose. However, no differences in discrimination were observed in an external validation based on a cohort of patients with HL treated from 1970 until 1986 from the Childhood Cancer Survivor Study.¹¹ These unexpected results may be explained by uncertainty in radiation dosimetry for breast segments of historic patients. Other organs, such as the lungs, might vary less in size and position between radiation fractions, and this may reduce uncertainty. In summary, our results confirm that BC risk estimates from a model using the mean breast dose were very similar to those based on more detailed radiation information.

In conclusion, we showed that modern RT exposing the breast, such as for HL, involves drastically lower radiation doses and irradiated volumes compared with treatments given before 2000 in a historic cohort of patients similar to those used in many prior studies of BC risk after HL. We observed higher absolute risk predictions 25 years after treatment based on quadrant-specific doses versus mean breast dose, although differences were small. Because the breasts of newly treated patients are still exposed to radiation levels for which increased BC risk is expected, the role of RT in the treatment of HL needs to be continuously evaluated. Using doses to the breast quadrants may improve the transportability of risk predictions to modern techniques. Therefore, we recommend using the quadrant-specific model. Further research is needed to evaluate whether this is the case for tumor sites other than the breast.

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