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Apr 25th, 2018
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  1. /**
  2. * 用來判斷來自 STAGING WORKUP 階段的狀態, 應該分派至何種 RECURRENCE RISK
  3. * @param state
  4. * @param model
  5. * @return next state
  6. */
  7. public static State recurrenceRiskStrategy(State state, Model model) {
  8. if(model.isBetweenClinicalStages("T1", "T2a") && model.isBetweenGleasonScore(2, 6) && model.getPsa() < 10){
  9. return new LowT1T2aGScore26PsaLt10(state, model);
  10. }
  11. if(model.isBetweenClinicalStages("T2b", "T2c") || model.isEqualGlessonScore(7) || model.isBetweenPsa(10, 20)){
  12. return new IntermediateT2bT2cOGScore7OPsa1020(state, model);
  13. }
  14. if(model.isContainsClinicalStage("T3a") || model.isBetweenGleasonScore(8, 10) || model.getPsa() > 20){
  15. return new HighT3aOGScore810OPsaGt20(state, model);
  16. }
  17. if(model.isBetweenClinicalStages("T3b", "T4")){
  18. return new LocallyAdvancedVerHighT3bT4(state, model);
  19. }
  20. if(model.isContainsClinicalStage("T") && model.isContainsClinicalStage("N1") ){
  21. return new MetastaticAnyTAndN1(state, model);
  22. }
  23. if(model.isContainsClinicalStage("T") && model.isContainsClinicalStage("N") && model.isContainsClinicalStage("M1")){
  24. return new AnyTAndAnyNAndM1(state, model);
  25. }
  26.  
  27. return new NullState(state, model);
  28. }
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