nciatwp-878: implement glossary changes

.gitignore

@@ -15,6 +15,7 @@ local.properties
 .classpath
 .settings/
 .loadpath
+common
 
 # External tool builders
 .externalToolBuilders/

biomarkerTools/biomarkerTools.py

@@ -8,15 +8,12 @@
 from sampleSize.sampleSize import *
 
 from flask import Flask, url_for
-app = Flask(__name__, static_folder='', static_url_path='/')
+app = Flask(__name__, static_folder='', static_url_path='')
 
 @app.route('/')
 @app.route('/biomarkerToolsRest')
 def index():
-    return render_template('index.html')
-
-def api_tool_calls():
-    return 'List of calls: '
+    return app.send_static_file('index.html')
 
 @app.route('/ping/', strict_slashes=False)
 def ping():

biomarkerTools/glossary.js

@@ -1,7 +1,8 @@
 $.extend($_Glossary,{
 	AUC : {
-		fullName : "Area under the receiver operator characteristic curve",
-		definition : " for a biomarker is the average sensitivity (or, equivalently, the integral of the sensitivity) in the interval of cSpecificity from 0 to 1 (specificity from 1 to 0), itself equal to the area between the ROC curve and the x-axis."
+		fullName : "Area under the receiver operator characteristic curve (AUC)",
+		definition : "Area under the receiver operator characteristic curve (AUC) for a biomarker is the average sensitivity (or, equivalently, the integral of the sensitivity) in the interval of cSpecificity from 0 to 1 (specificity from 1 to 0), itself equal to the area between the ROC curve and the x-axis. For a binary biomarker with Youden’s index J, the AUC = (1+J)/2 (this AUC formula is used by Mean Risk Stratification).",
+		glossaryDefinition : "For a biomarker is the average sensitivity (or, equivalently, the integral of the sensitivity) in the interval of cSpecificity from 0 to 1 (specificity from 1 to 0), itself equal to the area between the ROC curve and the x-axis. For a binary biomarker with Youden’s index J, the AUC = (1+J)/2 (this AUC formula is used by Mean Risk Stratification)."
 	},
 	cNPV : {
 		fullName : "Complement of Negative Predictive Value (cNPV)",
@@ -41,15 +42,15 @@ $.extend($_Glossary,{
 	},
   max_mrs: {
     fullName: "Maximum possible MRS for a disease with this prevalence",
-    definition: "Maximum possible MRS for a disease with this prevalence. Formula: max risk strat=2q(1-q)."
+    definition: "Denoting disease prevalence as q, MRS=2q(1-q)J, where J is Youden’s index. MRS is maximized when J=1. Thus the maximum MRS is 2q(1-q). Youden’s index is the fraction of maximum risk stratification for the disease that is achieved by the biomarker."
   },
   m_neg: {
     fullName: "Marker Negativity (M-)",
     definition: "Negative test result for biomarker test."
   },
   mrs: {
     fullName: "Mean Risk Stratification (MRS)",
-    definition: "Average change in pretest-posttest disease risk. Formula: MRS=2(ad-bc), where a,b,c,d are the joint probabilities inside a 2x2 table."
+    definition: "MRS is the average difference between predicted post-test individual risk and population-average (pre-test) risk. Simply, MRS is the average change in risk revealed by the test. Formula: MRS=2(ad-bc), where a,b,c,d are the joint probabilities inside a 2x2 table."
   },
   nnr: {
     fullName: "Number Needed to Recruit",
@@ -115,7 +116,11 @@ $.extend($_Glossary,{
 	Spec : {
 		fullName : "Specificity",
 		definition : "Specificity is the proportion whose biomarker test is negative (below the threshold) among those without disease."
-	}
+  },
+  Youden: {
+    fullName: "Youden's Index",
+    definition: "Youden's index (J) is the sum of sensitivity and specificity, minus 1. Denoting disease prevalence as q, MRS=2q(1-q)J, and thus Youden’s index is also the fraction of maximum risk stratification for the disease that is achieved by the biomarker."
+  }
 });
 $.extend($_Glossary, {
   cnpv: $_Glossary.cNPV,

biomarkerTools/help/help.js

@@ -13,7 +13,9 @@ $(document).ready(function(){
     keys = keys.sort();
     for (var index in keys) {
       index = keys[index];
-      $("<p><b>" + terms[index].fullName + ":</b><span> " + terms[index].definition + "</span></p>").appendTo(glossary);
+      $("<p><b>" + terms[index].fullName + ":</b><span> " +
+        (terms[index].glossaryDefinition || terms[index].definition) +
+        "</span></p>").appendTo(glossary);
     }
 });
 

biomarkerTools/src/app/pug/pages/meanRiskStratification.pug

@@ -248,13 +248,13 @@
           td.r_diff_result.output_field.bm_3
         tr
           td.text-left
-            | Youden's Index (YI)
+            a.define(href="javascript:void(0);", data-term="Youden") Youden's Index (J)
           td.youden_result.output_field.bm_1
           td.youden_result.output_field.bm_2
           td.youden_result.output_field.bm_3
         tr
           td.text-left
-            a.define(href="javascript:void(0);", data-term="AUC") AUC = (1+YI)/2
+            a.define(href="javascript:void(0);", data-term="AUC") AUC = (1+J)/2
           td.auc_result.output_field.bm_1
           td.auc_result.output_field.bm_2
           td.auc_result.output_field.bm_3

biomarkerTools/src/app/scripts/glossary.js

@@ -1,7 +1,8 @@
 $.extend($_Glossary,{
 	AUC : {
-		fullName : "Area under the receiver operator characteristic curve",
-		definition : " for a biomarker is the average sensitivity (or, equivalently, the integral of the sensitivity) in the interval of cSpecificity from 0 to 1 (specificity from 1 to 0), itself equal to the area between the ROC curve and the x-axis."
+		fullName : "Area under the receiver operator characteristic curve (AUC)",
+		definition : "Area under the receiver operator characteristic curve (AUC) for a biomarker is the average sensitivity (or, equivalently, the integral of the sensitivity) in the interval of cSpecificity from 0 to 1 (specificity from 1 to 0), itself equal to the area between the ROC curve and the x-axis. For a binary biomarker with Youden’s index J, the AUC = (1+J)/2 (this AUC formula is used by Mean Risk Stratification).",
+		glossaryDefinition : "For a biomarker is the average sensitivity (or, equivalently, the integral of the sensitivity) in the interval of cSpecificity from 0 to 1 (specificity from 1 to 0), itself equal to the area between the ROC curve and the x-axis. For a binary biomarker with Youden’s index J, the AUC = (1+J)/2 (this AUC formula is used by Mean Risk Stratification)."
 	},
 	cNPV : {
 		fullName : "Complement of Negative Predictive Value (cNPV)",
@@ -41,15 +42,15 @@ $.extend($_Glossary,{
 	},
   max_mrs: {
     fullName: "Maximum possible MRS for a disease with this prevalence",
-    definition: "Maximum possible MRS for a disease with this prevalence. Formula: max risk strat=2q(1-q)."
+    definition: "Denoting disease prevalence as q, MRS=2q(1-q)J, where J is Youden’s index. MRS is maximized when J=1. Thus the maximum MRS is 2q(1-q). Youden’s index is the fraction of maximum risk stratification for the disease that is achieved by the biomarker."
   },
   m_neg: {
     fullName: "Marker Negativity (M-)",
     definition: "Negative test result for biomarker test."
   },
   mrs: {
     fullName: "Mean Risk Stratification (MRS)",
-    definition: "Average change in pretest-posttest disease risk. Formula: MRS=2(ad-bc), where a,b,c,d are the joint probabilities inside a 2x2 table."
+    definition: "MRS is the average difference between predicted post-test individual risk and population-average (pre-test) risk. Simply, MRS is the average change in risk revealed by the test. Formula: MRS=2(ad-bc), where a,b,c,d are the joint probabilities inside a 2x2 table."
   },
   nnr: {
     fullName: "Number Needed to Recruit",
@@ -115,7 +116,11 @@ $.extend($_Glossary,{
 	Spec : {
 		fullName : "Specificity",
 		definition : "Specificity is the proportion whose biomarker test is negative (below the threshold) among those without disease."
-	}
+  },
+  Youden: {
+    fullName: "Youden's Index",
+    definition: "Youden's index (J) is the sum of sensitivity and specificity, minus 1. Denoting disease prevalence as q, MRS=2q(1-q)J, and thus Youden’s index is also the fraction of maximum risk stratification for the disease that is achieved by the biomarker."
+  }
 });
 $.extend($_Glossary, {
   cnpv: $_Glossary.cNPV,

biomarkerTools/src/app/scripts/help/help.js

@@ -13,7 +13,9 @@ $(document).ready(function(){
     keys = keys.sort();
     for (var index in keys) {
       index = keys[index];
-      $("<p><b>" + terms[index].fullName + ":</b><span> " + terms[index].definition + "</span></p>").appendTo(glossary);
+      $("<p><b>" + terms[index].fullName + ":</b><span> " +
+        (terms[index].glossaryDefinition || terms[index].definition) +
+        "</span></p>").appendTo(glossary);
     }
 });