{

 "cells": [

  {

   "attachments": {},

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   "source": [

    "# USPSTF recommendations notebook\n",

    "\n",

    "P. Benveniste $^1$, J. Alberge $^1$\n",

    "\n",

    "$^1$ Ecole Normale Supérieure Paris-Saclay\n",

    "\n",

    "In this Notebook, we look at the results of the USPSTF recommendations on PLCO and NLST. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 1,

   "metadata": {},

   "outputs": [],

   "source": [

    "#Import of the librairies\n",

    "import pandas as pd\n",

    "import numpy as np\n",

    "import matplotlib.pyplot as plt\n",

    "from tabulate import tabulate"

   ]

  },

  {

   "attachments": {},

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "We now import both datasets."

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 2,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "(55161, 10)\n",

      "(48595, 10)\n"

     ]

    }

   ],

   "source": [

    "#Loading of both datasets\n",

    "plco_file = './preprocessed_plco.csv'\n",

    "plco = pd.read_csv(plco_file)\n",

    "nlst_file = './preprocessed_nlst.csv'\n",

    "nlst = pd.read_csv(nlst_file)\n",

    "\n",

    "total_plco = len(plco)\n",

    "print(plco.shape)\n",

    "total_nlst = len(nlst)\n",

    "print(nlst.shape)"

   ]

  },

  {

   "attachments": {},

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "##### US RECOMMENDATION TOOL\n",

    "\n",

    "Now we look into the USPSTF recommendation tool on PLCO and NLST."

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 3,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Pre-processed PLCO size: 55161\n",

      "Pre-processed PLCO with lung cancer: 2752\n",

      "Patients from PLCO who fit into US recommendation: 22609\n",

      "Patients from PLCO who fit into US recommendation with lung cancer: 2105\n",

      "------- USPSTF RECOMMENDATION ON PLCO --------\n",

      "TP :  2105\n",

      "FN :  647\n",

      "TN :  31905\n",

      "FP :  20504\n",

      "Precision :  0.093\n",

      "Recall :  0.765\n"

     ]

    }

   ],

   "source": [

    "print(\"Pre-processed PLCO size:\", len(plco))\n",

    "print(\"Pre-processed PLCO with lung cancer:\", len(plco[plco[\"lung_cancer\"]==1]))\n",

    "\n",

    "plco_criteria = plco.copy()\n",

    "plco_criteria = plco_criteria[plco_criteria[\"age\"]>=50]\n",

    "plco_criteria = plco_criteria[plco_criteria[\"age\"]<=80]\n",

    "plco_criteria = plco_criteria[plco_criteria[\"pack_years\"]>=20]\n",

    "plco_criteria = plco_criteria[ (plco_criteria[\"cig_stat\"]==1) | (plco_criteria[\"age\"] - plco_criteria[\"ssmokea_f\"] <=15) ]\n",

    "\n",

    "print(\"Patients from PLCO who fit into US recommendation:\", len(plco_criteria))\n",

    "print(\"Patients from PLCO who fit into US recommendation with lung cancer:\", len(plco_criteria[plco_criteria[\"lung_cancer\"]==1]))\n",

    "\n",

    "TP_plco = len(plco_criteria[plco_criteria[\"lung_cancer\"]==1])\n",

    "FN_plco = len(plco[plco[\"lung_cancer\"]==1])-TP_plco\n",

    "TN_plco = len(plco[plco[\"lung_cancer\"]==0]) - len(plco_criteria[plco_criteria[\"lung_cancer\"]==0])\n",

    "FP_plco = len(plco_criteria[plco_criteria[\"lung_cancer\"]==0])\n",

    "\n",

    "print(\"------- USPSTF RECOMMENDATION ON PLCO --------\")\n",

    "print(\"TP : \", TP_plco)\n",

    "print(\"FN : \", FN_plco)\n",

    "print(\"TN : \", TN_plco)\n",

    "print(\"FP : \", FP_plco)\n",

    "print(\"Precision : \",  round(TP_plco/(TP_plco+FP_plco),3))\n",

    "print(\"Recall : \", round(TP_plco/(TP_plco+FN_plco),3) )"

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 4,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Pre-processed NLST size: 48595\n",

      "Pre-processed NLST with cancer: 1511\n",

      "Patients from NLST who fit into US recommendation: 48034\n",

      "Patients from NLST who fit into US recommendation with cancer: 1495\n",

      "------- USPSTF RECOMMENDATION ON NLST --------\n",

      "TP :  1495\n",

      "FN :  16\n",

      "TN :  545\n",

      "FP :  46539\n",

      "Precision :  0.031\n",

      "Recall :  0.989\n"

     ]

    }

   ],

   "source": [

    "print(\"Pre-processed NLST size:\", len(nlst))\n",

    "print(\"Pre-processed NLST with cancer:\", len(nlst[nlst[\"lung_cancer\"]==1]))\n",

    "\n",

    "nlst_criteria = nlst.copy()\n",

    "nlst_criteria = nlst_criteria[nlst_criteria[\"age\"]>=50]\n",

    "nlst_criteria = nlst_criteria[nlst_criteria[\"age\"]<=80]\n",

    "nlst_criteria = nlst_criteria[nlst_criteria[\"pack_years\"]>=20]\n",

    "nlst_criteria = nlst_criteria[ (nlst_criteria[\"cig_stat\"]==1) | (nlst_criteria[\"age\"] - nlst_criteria[\"ssmokea_f\"] <=15) ]\n",

    "\n",

    "print(\"Patients from NLST who fit into US recommendation:\", len(nlst_criteria))\n",

    "print(\"Patients from NLST who fit into US recommendation with cancer:\", len(nlst_criteria[nlst_criteria[\"lung_cancer\"]==1]))\n",

    "\n",

    "TP_nlst = len(nlst_criteria[nlst_criteria[\"lung_cancer\"]==1])\n",

    "FN_nlst = len(nlst[nlst[\"lung_cancer\"]==1])-TP_nlst\n",

    "TN_nlst = len(nlst[nlst[\"lung_cancer\"]==0]) - len(nlst_criteria[nlst_criteria[\"lung_cancer\"]==0])\n",

    "FP_nlst = len(nlst_criteria[nlst_criteria[\"lung_cancer\"]==0])\n",

    "\n",

    "print(\"------- USPSTF RECOMMENDATION ON NLST --------\")\n",

    "print(\"TP : \", TP_nlst)\n",

    "print(\"FN : \", FN_nlst)\n",

    "print(\"TN : \", TN_nlst)\n",

    "print(\"FP : \", FP_nlst)\n",

    "print(\"Precision : \",  round(TP_nlst/(TP_nlst+FP_nlst),3))\n",

    "print(\"Recall : \", round(TP_nlst/(TP_nlst+FN_nlst),3) )"

   ]

  },

  {

   "attachments": {},

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "### Saving a txt file\n",

    "\n",

    "Now we write a text file to concatenate these analyses. "

   ]

  },

  {

   "cell_type": "code",

   "execution_count": 5,

   "metadata": {},

   "outputs": [

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "File edited\n"

     ]

    }

   ],

   "source": [

    "with open('./USPSTF_recommendations.txt', 'w') as f:\n",

    "    f.write('------------ COMPARISON WITH USPSTF ON PLCO------------ \\n \\n')\n",

    "    f.write(\"Pre-processed PLCO size: \" +str(len(plco)) + '\\n')\n",

    "    f.write(\"Pre-processed PLCO with lung cancer: \" + str(len(plco[plco[\"lung_cancer\"]==1])) + '\\n')\n",

    "    f.write(\"Patients from PLCO who fit into US recommendation: \"+ str(len(plco_criteria))+ '\\n')\n",

    "    f.write(\"Patients from PLCO who fit into US recommendation with lung cancer: \"+ str(len(plco_criteria[plco_criteria[\"lung_cancer\"]==1])) + '\\n\\n')\n",

    "    f.write(\"------- USPSTF RECOMMENDATION ON PLCO -------- \\n\")\n",

    "    f.write(\"TP : \" + str(TP_plco) + '\\n')\n",

    "    f.write(\"FN : \" + str(FN_plco) + '\\n')\n",

    "    f.write(\"TN : \" + str(TN_plco) + '\\n')\n",

    "    f.write(\"FP : \" + str(FP_plco) + '\\n')\n",

    "    f.write(\"Precision : \" +  str(round(TP_plco/(TP_plco+FP_plco),3)) + '\\n')\n",

    "    f.write(\"Recall : \" + str(round(TP_plco/(TP_plco+FN_plco),3)) + '\\n\\n\\n')\n",

    "    f.write('------------ COMPARISON WITH USPSTF ON NLST------------ \\n \\n')\n",

    "    f.write(\"Pre-processed NLST size: \" +str(len(nlst)) + '\\n')\n",

    "    f.write(\"Pre-processed NLST with lung cancer: \" + str(len(nlst[nlst[\"lung_cancer\"]==1])) + '\\n')\n",

    "    f.write(\"Patients from NLST who fit into US recommendation: \"+ str(len(nlst_criteria))+ '\\n')\n",

    "    f.write(\"Patients from NLST who fit into US recommendation with lung cancer: \"+ str(len(nlst_criteria[nlst_criteria[\"lung_cancer\"]==1])) + '\\n\\n')\n",

    "    f.write(\"------- USPSTF RECOMMENDATION ON NLST -------- \\n\")\n",

    "    f.write(\"TP : \" + str(TP_nlst) + '\\n')\n",

    "    f.write(\"FN : \" + str(FN_nlst) + '\\n')\n",

    "    f.write(\"TN : \" + str(TN_nlst) + '\\n')\n",

    "    f.write(\"FP : \" + str(FP_nlst) + '\\n')\n",

    "    f.write(\"Precision : \" +  str(round(TP_nlst/(TP_nlst+FP_nlst),3)) + '\\n')\n",

    "    f.write(\"Recall : \" + str(round(TP_nlst/(TP_nlst+FN_nlst),3)) + '\\n\\n\\n')\n",

    "print(\"File edited\")"

   ]

  }

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