Utility of a Cancer Predisposition Screening Tool for Predicting Subsequent Malignant Neoplasms in Childhood Cancer Survivors Academic Article uri icon

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abstract

  • PURPOSE Childhood cancer survivors (CCS) are at risk of developing subsequent malignant neoplasms (SMNs) resulting from exposure to prior therapies. CCS with underlying cancer predisposition syndromes are at additional genetic risk of SMN development. The McGill Interactive Pediatric OncoGenetic Guidelines (MIPOGG) tool identifies children with cancer at increased likelihood of having a cancer predisposition syndrome, guiding clinicians through a series of Yes or No questions that generate a recommendation for or against genetic evaluation. We evaluated MIPOGG's ability to predict SMN development in CCS. METHODS Using the provincial cancer registry (Ontario, Canada), and adopting a nested case-control approach, we identified CCS diagnosed and/or treated for a primary malignancy before age 18 years (1986-2015). CCS who developed an SMN (cases) were matched, by primary cancer and year of diagnosis, with CCS who did not develop an SMN (controls) over the same period (1:5 ratio). Potential predictors for SMN development (chemotherapy, radiation, and MIPOGG output) were applied retrospectively using clinical data pertaining to the first malignancy. Conditional logistic regression models estimated hazard ratios and 95% CIs associated with each covariate, alone and in combination, for SMN development. RESULTS Of 13,367 children with a primary cancer, 317 (2.4%) developed an SMN and were matched to 1,569 controls. A MIPOGG output recommending evaluation was significantly associated with SMN development (hazard ratio 1.53; 95% CI, 1.06 to 2.19) in a multivariable model that included primary cancer therapy exposures. MIPOGG was predictive of SMN development, showing value in nonhematologic malignancies and in CCS not exposed to radiation. CONCLUSION MIPOGG has additional value for SMN prediction beyond treatment exposures and may be beneficial in decision making for enhanced individualized SMN surveillance strategies for CCS.

authors

  • Cullinan, Noelle
  • Schiller, Ian
  • Di Giuseppe, Giancarlo
  • Mamun, Mohammed
  • Reichman, Lara
  • Cacciotti, Chantel
  • Wheaton, Laura
  • Caswell, Kimberly
  • Di Monte, Bruna
  • Gibson, Paul
  • Johnston, Donna L
  • Fleming, Adam
  • Pole, Jason D
  • Malkin, David
  • Foulkes, William D
  • Dendukuri, Nandini
  • Goudie, Catherine
  • Nathan, Paul C

publication date

  • October 10, 2021