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Second primary malignancy risk in thyroid cancer and matched patients with and without radioiodine therapy analysis from the observational health data sciences and informatics

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Abstract

Purpose

Risk of second primary malignancy (SPM) after radioiodine (RAI) therapy has been continuously debated. The aim of this study is to identify the risk of SPM in thyroid cancer (TC) patients with RAI compared with TC patients without RAI from matched cohort.

Methods

Retrospective propensity-matched cohorts were constructed across 4 hospitals in South Korea via the Observational Health Data Science and Informatics (OHDSI), and electrical health records were converted to data of common data model. TC patients who received RAI therapy constituted the target group, whereas TC patients without RAI therapy constituted the comparative group with 1:1 propensity score matching. Hazard ratio (HR) by Cox proportional hazard model was used to estimate the risk of SPM, and meta-analysis was performed to pool the HRs.

Results

Among a total of 24,318 patients, 5,374 patients from each group were analyzed (mean age 48.9 and 49.2, women 79.4% and 79.5% for target and comparative group, respectively). All hazard ratios of SPM in TC patients with RAI therapy were ≤ 1 based on 95% confidence interval(CI) from full or subgroup analyses according to thyroid cancer stage, time-at-risk period, SPM subtype (hematologic or non-hematologic), and initial age (< 30 years or ≥ 30 years). The HR within the target group was not significantly higher (< 1) in patients who received over 3.7 GBq of I-131 compared with patients who received less than 3.7 GBq of I-131 based on 95% CI.

Conclusion

There was no significant difference of the SPM risk between TC patients treated with I-131 and propensity-matched TC patients without I-131 therapy.

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Data access, responsibility, and analysis

Ho-Young Lee and Sooyoung Yoo had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

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Funding

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI) and was funded by the Ministry of Health & Welfare, Republic of Korea (grand number: HI19C0378).

Author information

Author notes

  1. S. Kim and J-I Bang contributed equally in this work.

Authors and Affiliations

  1. Office of eHealth Research and Business, Seoul National University Bundang Hospital, 173rd Street, Gumi-ro, Seongnam-si 436-707, Republic of Korea

    Seok Kim, Dachung Boo, Borham Kim & Sooyoung Yoo

  2. Department of Nuclear Medicine, CHA Bundang Medical Center, CHA University, Seongnam, Republic of Korea

    Ji-In Bang

  3. Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

    In Young Choi & SooJeong Ko

  4. Department of Biomedicine & Health Sciences, The Catholic University of Korea, Seoul, Republic of Korea

    SooJeong Ko

  5. Division of Nuclear Medicine, Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea

    Ie Ryung Yoo

  6. Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea

    Kwangsoo Kim

  7. Medical Big Data Research Center, Seoul National University Medical Research Center, Seoul, Republic of Korea

    Kwangsoo Kim

  8. Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Republic of Korea

    Junmo Kim

  9. Biomedical Research Institute, Seoul National University Hospital, Seoul, South Korea

    YoungHwan Joo

  10. Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea

    Hyun Gee Ryoo

  11. Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea

    Jin Chul Paeng

  12. Department of Nuclear Medicine, Soonchunhyang University Bucheon Hospital, Gyeonggido, Republic of Korea

    Jung Mi Park

  13. Department of Statistics, Seoul National University, Seoul, South Korea

    Woncheol Jang, Yangha Chung & Dongyoon Yang

  14. Department of Statistics, Kyungpook National University, Daegu, South Korea

    Byungwon Kim

  15. Department of Nuclear Medicine, Office of eHealth Research and Business, Seoul National University Bundang Hospital, 166, Gumi-ro, Seongnam-si 436-707, Republic of Korea

    Ho-Young Lee

Authors
  1. Seok Kim
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  2. Ji-In Bang
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Contributions

Seok Kim was involved in the data curation; formal analysis; methodology; writing—original draft; writing—review and editing.

Ji-In Bang contributed to the formal analysis; writing—original draft; writing—review and editing.

Dachung Boo contributed to the data curation; formal analysis; methodology; writing—review and editing.

Borham Kim helped in the data curation; formal analysis; writing—review and editing.

In Young Choi contributed to the data curation; formal analysis; methodology; writing—review and editing.

SooJeong Ko was involved in the data curation; formal analysis; methodology; writing—review and editing.

Ie Ryung Yoo was involved in the data curation; writing—review and editing.

Kwangsoo Kim contributed to the methodology; formal analysis; writing—review and editing.

Junmo Kim helped in the methodology; formal analysis; writing—review and editing.

YoungHwan Joo contributed to the methodology; formal analysis; writing—review and editing.

Hyun Gee Ryoo contributed to the data curation; writing—review and editing.

Jin Chul Paeng was involved in the data curation; writing—review and editing.

Jung Mi Park helped in the data curation; writing—review and editing.

Woncheol Jang was involved in the methodology; formal analysis; writing—review and editing.

Byungwon Kim contributed to the formal analysis; writing—review and editing.

Yangha Chung contributed to the formal analysis; writing—review and editing.

Dongyoon Yang was involved in the formal analysis; writing—review and editing.

Sooyoung Yoo was involved in the conceptualization; investigation; supervision; writing—review and editing.

Ho-Young Lee helped in the conceptualization; investigation; supervision; writing—review and editing.

Corresponding authors

Correspondence to Sooyoung Yoo or Ho-Young Lee.

Ethics declarations

Ethics approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Consent to participate

Informed consent was waived by the institutional review boards of Seoul National University Bundang Hospital, Seoul National University Hospital, Seoul St. Mary’s Hospital of Catholic University, and Soonchunhyang University Hospital Bucheon in the retrospective nature of the study, and all the procedures being performed were part of the routine care.

Consent to publish

Not applicable.

Competing interest

Seok Kim, Ji-In Bang, Dachung Boo, Borham Kim, In Young Choi, SooJeong Ko, Ie Ryung Yoo, Kwangsoo Kim, Junmo Kim, YoungHwan Joo, Hyun Gee Ryoo, Jin Chul Paeng, Jung Mi Park, Woncheol Jang, Byungwon Kim, Yangha Chung, Dongyoon Yank, Sooyoung Yoo, and Ho-Young Lee declare that there are no conflicts of interest.

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This article is part of the Topical Collection on Oncology - Head and Neck

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Kim, S., Bang, JI., Boo, D. et al. Second primary malignancy risk in thyroid cancer and matched patients with and without radioiodine therapy analysis from the observational health data sciences and informatics. Eur J Nucl Med Mol Imaging 49, 3547–3556 (2022). https://doi.org/10.1007/s00259-022-05779-9

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