Sequential drug decision problems in long-term medical conditions: a case Study of Primary Hypertension Eunju Kim ba, ma, msc

Function [TNB] = EvModel(Policy,Scenario)
% Redefine the key variables from the scenario.

T = Scenario.drug_switching_period; % Drug switching period.

Age = Scenario.initial_age; % Initial age.

iSBP = Scenario.initial_SBP; % Initial SBP.

cLength = Scenario.cycle_length; % Cycle length.

Sample = Scenario.number_of_repetitions; % The no. of PSA runs.

WTP = Scenario.WTP; % Willingness-to-pay.
% Generate the decision tree by the scenario defined.

dTree = TreeGenerator(Scenario);

% Generate the index of the location of the drug used for h at t, where a specific policy is given.

DrugIdx = VarsGenerator(dTree);

% Generate whether a maintenance therapy is used, if so, how long the maintenance therapy has been used.

Maintenance = MTGenerator(dTree);

% Defined the memory variables for the use in the next period.

pTrtSux = zeros(size(dTree,1),T); % Treatment success rate.

SBP = zeros(size(dTree,1),T); SBP(1,1) = iSBP; % SBP

SBPSD = zeros(size(dTree,1),T); SBPSD(1,1) = 21.1; % The SD of SBP.

pCVD = zeros(size(dTree,1),T+1); % The probability of CVDs.

pHF = zeros(size(dTree,1),T+1); % The probability of HF.

pDM = zeros(size(dTree,1),T+1); % The probability of DM.

pAE = zeros(size(dTree,1),T); % The probability of AEs.

% Initialise the state transition matrix for the patients who stay in the short-term drug switching model.

pDizPath = zeros(size(dTree,1),T+1); pDizPath(1,1) = 1;

% Initialise the matrices for the short-term costs and QALYs calculated from h at t.

STCosts = zeros(size(dTree,1),T);

STQALYs = zeros(size(dTree,1),T);
% Each group of patients who move to the long-term CVD model from h at t has their own matrices for the long-term state transition probabilities, costs and QALYs.

LTProb = cell(t,h);

LTCost = cell(t,h);

LTQaly = cell(t,h);

% The cumulated state transition probabilities, costs and QALYs for all those patients who moved to the long-term model.

CumLTProb = zeros((104-Age)+1,11);

CumLTCost = zeros((104-Age)+1,11);

CumLTCQALY = zeros((104-Age)+1,11);

% Call datasets.

[cEvent,cDrug,distCVD,pNonCVDd] = Data(Scenario);