{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Survival Analysis\n", "\n", "This is a detailed guide for using DNAMite for survival analysis." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### What is Survival Analysis?\n", "\n", "In survival analysis, the goal is to predict the *survival probability* $P(T > t)$, or equivalently the *cumulative incidence function* (CIF) $P(T \\leq t)$ for some time-to-event random variable $T$. Survival analysis is somewhat similar to binary classification, but instead of predicting a single probability (e.g. $P(T > t)$ for a single $t > 0$), we want to estimate the entire distribution, i.e. the survival probability at all times $t \\in \\mathbb{R}$. Survival analysis is very common in healthcare (e.g. when $T$ is mortality time or time-until-diagnosis), but appears in many domains such as customer churn, engineering, and actuarial science. \n", "\n", "In survival analysis models, we are usually given a set of features $X$ and asked to estimate the conditional distribution $T \\mid X$, for example by estimating the conditional CIF $P(T \\leq t \\mid X)$. Survival analysis problems are also often complicated by *censoring* of some samples. When a dataset encounters censoring, a. second time-to-event random variable $C$ denotes the censoring time of patients, and we only are given the following two random variables:\n", "\n", "1) $Z = \\text{min}(T, C)$: the observed event time.\n", "2) $\\delta = \\mathcal{1}_{C > T}$: the indicator if the sample is censored (0) or not (1).\n", "\n", "Thus, we observe data of the form $(X_i, Z_i, \\delta_i), i= 1, 2, \\ldots, n$ and from this data we would like to estimate $P(T \\leq t \\mid X)$. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### dnamite for Survival Analysis\n", "\n", "For an overview of the methodology used to fit a dnamite model in general, see the [Why dnamite User Guide](https://dnamite.readthedocs.io/en/latest/notebooks/user_guides/why_dnamite.html).\n", "\n", "A dnamite survival analysis model outputs $K$ predictions $\\hat{P}(T \\leq t_1 \\mid X), \\ldots, \\hat{P}(T \\leq t_K \\mid X)$ corresponding to $K$ evaluation times $t_1, \\ldots, t_K$. These predictions are optimized using the Inverse Probability of Censoring Weighting (IPCW) loss: $$ \\sum_{i=1}^n \\sum_{k=1}^K \\frac{1_{Z_i > t_k} \\hat{P}(T \\leq t_k \\mid X)^2}{\\hat{P}(C > t_k)} + \\frac{1_{Z_i \\leq t_k, \\delta_i = 1} (1 - \\hat{P}(T \\leq t_k \\mid X))^2}{\\hat{P}(C > Z_i)}. $$ Let's break down this loss a little bit: \n", "\n", "- The indicator in the first term $1_{Z_i > t_k}$ only is 1 when the observed event time is greater than $t_k$. When $Z_i > t_k$ we also know that $T_i > t_k$ by definition, so it makes sense to minimize $\\hat{P}(T \\leq t_k \\mid X)$ in these cases. \n", "- On the other hand, the indicator in the second term $1_{Z_i \\leq t_k, \\delta_i = 1}$ is 1 only when the true event is known to have occurred before time $t_k$. In these cases, it makes sense to maximize $\\hat{P}(T \\leq t_k \\mid X)$.\n", "- The denominator terms use an estimate for the survival function of the censoring time $C$. dnamite obtains this estimate by fitting a Kaplan-Meier model to the censoring distribution before the start of model training.\n", "\n", "By producing time-dependent predictions, dnamite differs from many survival analysis models that produce time-independent risk scores trained using the Cox loss. This allows dnamite to more accurately capture the entire time-to-event distribution. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Training a dnamite Survival Model\n", "\n", "dnamite follows the conventions used in [scikit-survival](https://scikit-survival.readthedocs.io/en/stable/index.html) for preparing survival analysis data. Survival labels should be stored in a numpy structured array with dype `np.dtype([('event', bool), ('time', float)])`, where `event` is True only when the sample is not censored and `time` is the event/censor time.\n", "\n", "For this guide we will use the SUPPORT dataset [1], a standard dataset for survival analysis. The support dataset estimates the mortality risk of critically ill hospital patients. We will pull the data from the [UCI repository](https://archive.ics.uci.edu/dataset/880/support2) where more dataset details can be found.\n", "\n", "[1] Knaus, William A., et al. \"The SUPPORT prognostic model: Objective estimates of survival for seriously ill hospitalized adults.\" Annals of internal medicine 122.3 (1995): 191-203." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Percent of samples that are censored: 0.3189456342668863\n" ] } ], "source": [ "import numpy as np \n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "sns.set_theme()\n", "from ucimlrepo import fetch_ucirepo \n", " \n", "support2 = fetch_ucirepo(id=880) \n", "X = support2.data.features \n", "y = np.empty(len(X), dtype=[('event', 'bool'), ('time', 'float32')])\n", "y['event'] = support2.data.original[\"death\"]\n", "y['time'] = support2.data.original[\"d.time\"]\n", "\n", "print(\"Percent of samples that are censored: \", np.mean(~y['event']))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that roughly 30\\% of samples in the dataset are censored, which means that roughly 30\\% of patients in the dataset do not die before the end of data collection." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Fitting a dnamite survival model is then the same as fitting a regression of classification model." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=10)\n", "\n", "from dnamite.models import DNAMiteSurvival\n", "model = DNAMiteSurvival(random_state=0)\n", "model.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Evaluating Survival Models\n", "\n", "The most common metric for evaluating survival analysis models is concordance index or C-index, which is similar to AUC but robust to censoring. The C-index is defined as:\n", "\n", "$$\n", "\\frac{\\sum_{i, j} 1(Z_i < Z_j) \\cdot 1(r_i > r_j)}{\\sum_{i, j} 1(t_i < t_j)}\n", "$$\n", "\n", "where $r_i$ is the predicted risk score for sample $i$. From this definition it is evident that C-index only takes as input a single risk score for each sample. This is natural for models like Cox regression that output a single risk score, but for models like DNAMite that output time-dependent risk scores C-index is not an appropriate metric. Thus, we recommend evaluating DNAMite using the [time-dependent AUC](https://scikit-survival.readthedocs.io/en/stable/api/generated/sksurv.metrics.cumulative_dynamic_auc.html) metric implemented in scikit-survival. The [scikit-survival evaluation guide](https://scikit-survival.readthedocs.io/en/stable/user_guide/evaluating-survival-models.html) is a great resource for learning more about different survival analysis metrics. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9065666480284704" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sksurv.metrics import cumulative_dynamic_auc\n", "\n", "test_times = np.linspace(30, 365*4, 100)\n", "cdf_preds = 1 - model.predict_survival(X_test, test_times=test_times)\n", "_, mean_auc = cumulative_dynamic_auc(y_train, y_test, cdf_preds, test_times)\n", "mean_auc" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Time-dependent Interpretations\n", "\n", "Since DNAMite outputs time-dependent predictions, we can look at model interpretations at a specific evaluation point. For example, we can look at the feature importances for predicting mortality risk in the next year." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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O69v/srmuaNGiN0xw3rFjh9PGlR+++eYb27+tVitr1qyhVq1aeHh4UKdOHU6dOnXDFVQrVqzA3d2dGjVqZNnvv/dXYmIiR48e5emnnyYkJAQ3t2t/s/17P2dH7dq1SU9Pty17fexDhgxh9uzZhIaG4u7uztmzZzPtXzc3NyZNmsTJkyc5deoUjRs3tl2dV6lSJV577TUaNmzI6dOns1x3mTJl+PPPP7M91lttw4kTJzh8+LDttdTUVPr06XPD1YDw/0cG7T9v//6sNWjQgIyMjEw1TUtLY/Pmzbbvc/rZO3v2LK6urgQEBNx0O3bs2EG9evV49NFHbcFo7969nD9/PlNNszrKZ+/fbQICAjKN8d9f/v7+uLq6MnHiRCZOnJhp2V9//ZWkpCTb1WmNGzdm//79tgnxcO0zuXPnTmrVqgVcm08WHR3N0aNHbW0sFgsJCQm2P5qkcNGRI7kjubq60r9/f4YNG4arqytNmjTh4sWLzJgxg7Nnz9omc9eoUYOVK1dSvXp1Spcuzc6dO4mPj8dkMpGSkgJc+0sfYMuWLVSuXJnQ0FCaNGnC+vXrGTt2LE2bNmX79u3ZurIlu+PKD+PHjyc1NZWKFSuyaNEijhw5wscffwxA+/btWbhwIb169aJv374EBQWxfv16vvjiC3r37m07CnEzN9tfgYGBLFiwgNKlS+Pn58emTZuYN28egG0/Z0d4eDhhYWFER0fTr18/ypYty/Llyzly5AgjR47E39+fV199lalTp3L58mXq1avH2bNnmTp1KiaTifvvvx9fX19Kly7NqFGjuHz5MuXKlWPv3r1s3LiRiIiILNfdqFEjvvrqKy5dumTbRke0b9+eTz75hB49etC3b1/8/f2ZN28e6enptjtv22vcuDFjx45l2LBhvPLKK/z555+89957mSaGN2jQgIceeoi3336bf/75h8DAQObNm8f58+dtp/By+tnbsWMHtWvXzvJUYo0aNfjqq6/49NNPqVy5MgcOHGDmzJmZ/u/AtSNWO3fu5KeffqJ27do3nbvj5+fHrl272LJlC9WqVcv2kZo+ffowePBghg8fTosWLThx4gTTpk2jSpUqdOjQAYCuXbuyZMkSXn/9dfr374+Xl5dtnNcv5X/uuef47LPP6N69O2+88QZeXl4sXLiQQ4cO2W7rIYWLwpHcsTp27IiPjw/vv/8+n3/+Od7e3jz44INMmDCBsmXLAjBu3DhGjhxpu5tuhQoViImJYcWKFbZLfYsWLcrLL7/M559/zsaNG9m8eTMdOnTg+PHjLF26lM8++4w6deowbdo0nn/+eaeMKz+88847zJ49mxMnTlCtWjU+/PBD23wrLy8vPvnkEyZOnGgLGpUqVWL06NH/edfkm+2vGTNmMHr0aKKjo/Hw8ODee+9l5syZjBkzhu3bt99wz6isuLq6MmfOHCZMmMDUqVNJSUkhODiYDz/80HY0q1+/fpQsWZKFCxfy/vvvU6xYMRo0aMCAAQNsoWb69OlMmjSJqVOnkpiYyD333EPv3r1v+diMJk2a4ObmxqZNm2jZsmW2xpvV/pk/fz7jx49n5MiRWCwWatasybx58yhbtuwNp9wqVqzIu+++y8yZM3n99depXLlyps/sddOnT2fChAlMmzaN1NRUWrZsyTPPPMO6detsbbL72UtNTWXbtm3069cvy+2Ijo4mPT2dKVOmkJaWRlBQED169OC3335j/fr1tlN83bt3Z8aMGbz22musXr2aMmXK3NBXp06d2Lt3L6+99hpjx47lySefzNa+bNeuHZ6ensTHx7N8+XK8vb159NFHGThwoO2UWbFixfj000+JjY1lxIgRpKen8+CDD7Jw4ULuuece4Nrp1gULFjBx4kRGjRrFlStXCAkJYe7cuZkubpDCw2TV0/xExM6SJUsYMmQI69aty/bVV3LNyJEjOXz4sO2oV2G1bNkyJkyYwDfffHNb3yFbxFGacyQi4iTdu3fnwIED/PLLL0YPJc9YLBY+/PBDevfurWAkhZbCkYiIk5QsWZJ33nmHMWPGGD2UPPPFF19QsmRJnnvuOaOHIpJndFpNRERExI6OHImIiIjYUTgSERERsaNwJCIiImJH9zlykNVqxWLRdC0jubiYVAODqQbGUw2MpxoY72Y1cHExOfxAYIUjB5lMJi5eTCYjI/uPNhDncXNzwd/fRzUwkGpgPNXAeKqB8bKqQYkSPri6OhaOdFpNRERExI7CkYiIiIgdhSMREREROwpHIiIiInYUjkRERETsKByJiIiI2FE4EhEREbGjcCQiIiJiR+FIRERExI7CkYiIiIgdhSMREREROwpHIiIiInb04NlccHVVtjTK9X2vGhhHNTCeamC8glADi8V6wxPr5dZMVqtVe8wBVqsVk8mxp/2KiIjkF7PZQlJScqENSG5uLvj7+5CYeIWMDIvt9RIlfBwOrTpy5CCTycSEBTs4efaS0UMRERG5qaAAXyI71cLFxVRow1FeUDjKhZNnL3Hk1AWjhyEiIiJOdPueJBURERExgMKRiIiIiB2FIxERERE7CkciIiIidgpNOAoODmbJkiVGD0NEREQKuEITjkREREScQeFIRERExE6BvM/RmTNniImJYevWrfj6+jJo0CDbe3FxcezYsYOGDRsyf/58EhMTCQ0NJSYmhsqVKwPXTsH16tWLpUuXkp6ezvz586lQoYJBWyMiIgWZOSPV6CFkKSP9KsnJySQnJ2M2W/57AQN4eXkbPYQbFLhwlJGRwauvvkrRokWZP38+aWlpxMTEZGqzfft2ihQpQnx8POnp6URFRRETE8O8efNsbRYuXMicOXMwm80KRiIi4rDdi/sbPYQs7QaWTjN6FLe2d++hXC2fF8+3K3DhaMuWLRw+fJi1a9dSrlw5AMaOHUu7du1sbTIyMhg/fjzFihUD4LnnniM2NjZTP23btiUkJCTfxi0iIiI38vf3cUo/fn5eTukHCmA4OnToEMWKFbMFI4CqVavi6elp+/7uu++2BSMAX19f0tPTM/VTvnz5vB+siIgUeqFPTzZ6CFmqVMaP8X0e4eLFlNv2tFpi4pVcLe/q6oKfn9cN2+jn53XnPHjWZDJhsdxYYDe3/98UDw+P/+zHPkyJiIg4ytWtiNFDyJKbuyfe3t6kplozPbH+duKscZnNFqf1VeCuVqtatSqXLl3i8OHDttf++OMPLl++bOCoREREpLAocOGoXr16hIaGEhUVxc8//8yePXuIiorCxaXAbYqIiIjchgpconBxcWH27NlUqlSJbt26ERERQatWrShRooTRQxMREZFCwGS1Wq1GD6Kg6jdpA0dOXTB6GCIiIjdVObAYUwaEk5h45badc5Rbbm4u+Pv73LCNJUr4ODwhu8AdORIRERHJSwpHIiIiInYUjkRERETsFLj7HN1OggJ8jR6CiIhIlvR7yjGakO0gq9WKyWQyehgiIiK3ZDZbSEpKxmIpnL/u82JCto4cOchkMt3Wt2Mv7LK6XbzkH9XAeKqB8QpCDSwWa6ENRnlF4SgXnHmrcnGMamA81cB4qoHxVIPCRROyRUREROwoHImIiIjY0Wm1XHB0opfk3vV9rxoYx+gaaB6FiOQVhSMHWa1W/Py8jB7GHU81MJ5RNSjsV+CIiHEUjhxkMpmYsGAHJ89eMnooInecoABfIjvVwsXFpHAkIk6ncJQLJ89e0oNnRUREChlN2BARERGxo3AkIiIiYkfhSERERMSOwpGIiIiInds2HCUmJrJo0SLb9126dCE6OjpP+hYRERG57ra9Wm38+PGcPHmSjh07AhAXF4erq2ue9C0iIiJy3W0bjqzWzPcuKV68eJ71LSIiInJdnoajQ4cOMXHiRHbu3ElKSgoBAQF06tSJ5s2b07x5c2bPnk3jxo1t7YcMGcIff/xB+fLlWbp0KQDBwcEcPHiQLl26EBgYyLhx4zCbzUyaNIlVq1bxzz//EBQUxIsvvsjzzz8PwD///ENMTAzbtm0jJSWFatWqMWDAAOrWrUt0dPQNfYtI/jNnpDq8bEb6VZKTk0lOTsZsdvxJ6F5e3g4vKyKFV56Fo5SUFLp160ajRo347LPPcHV1ZdGiRbz77rs0aNCAOnXqsGrVKls4Sk1NZc2aNURHR9OiRQuuXr3KmTNniIuLu6HvhQsX8vXXXzN58mQCAgL49ttveeedd7jvvvuoXbs277zzDmlpacyfPx8PDw9mzZpFz549+e6773jrrbdu2beI5I/di/s7viywdFrux7B376Hcd2Igo59vJ6rB7SAvapCn4ahr16506tQJHx8fAPr27cv777/PwYMHad++PSNGjCAlJQUvLy/Wr1+P2WzmiSeeoGjRonh6euLu7k7JkiVv6Pv48eN4e3sTFBREqVKl6Ny5M5UqVaJixYq296tUqULZsmXx9PTkrbfe4sknn8TV1RVvb+9b9i0idw5/fx+jh+AUesag8VQD4zmzBnkWjkqUKMELL7zAqlWr2LdvH8ePH+fAgQMAWCwWWrRowYgRI1i3bh2tW7dmxYoVPProoxQtWvQ/++7UqRPffPMNjRs3pmrVqjRq1IhWrVpx1113AdC7d28GDRpEQkICtWrV4qGHHqJ169YUKVIkrzZXRHIo9OnJDi9bqYwf4/s8wsWLKbk6rZaYeMXhZW8Hrq4u+Pl55Xo/iONUA+NlVQM/Py+HjyblWTg6d+4czz77LCVKlKBp06Y89NBDhISE2E6jeXt706JFC1auXMlDDz3Epk2biI+Pz1bfFSpUYM2aNfz4449s3ryZDRs2MGfOHMaOHctTTz1F8+bN2bRpE5s2beKHH37go48+Yvr06fzvf//jvvvuy6tNFpEccHVz/I8VN3dPvL29SU21kpHh+C+k3Cx7OzGbLYVmWwoq1cB4zqxBnoWjVatWkZSUREJCAu7u7gC2yc/Xrxbr0KEDL730EsuWLePuu++mfv36tuVNJlOWfc+bN4+77rqLVq1a0ahRI6Kionj55ZdZvXo1rVq1YuLEibRt25aWLVvSsmVLrl69SqNGjdiwYQP33XffLfsWERGRO1uezSArXbo0KSkpfP3115w+fZrvv/+eAQMGAJCWlgZA7dq1ueeee5g2bRpt27bFxeX/h+Pt7c1ff/3FiRMnbuj7/PnztlNyp06dYtOmTezfv5+wsDA8PDzYs2cPQ4cO5eeff+bkyZMsWbKE5ORkwsLC/rNvERERubPl2ZGjFi1a8OuvvzJu3DguX75MYGAgHTt2ZN26dezZs8d22f1TTz3F1KlTad++fabl27Vrx9q1a2ndujVr1qzJ9F7v3r1JT09n1KhRnDt3jpIlS/L8888TEREBwOTJkxk7diw9evTg0qVLVKpUiQkTJlC7du2b9h0QEJBXu0FEREQKGJNVd0R0WL9JGzhy6oLRwxC541QOLMaUAeEkJl65o+d5uLm54O/vc8fvByOpBsbLqgYlSvg4PCFbN2YQERERsaNwJCIiImJH4UhERETEjsKRiIiIiJ08ffBsYRcU4Gv0EETuSPq/JyJ5SeHIQVarlchOtYwehsgdy2y2YLHoYlsRcT6FIweZTCY9S8dAep6R8YyugcViVTgSkTyhcJQLepaO8VQD46kGIlLYaEK2iIiIiB0dOcoFR++8Kbl3fd/fKTXQKSQRkfyjcOQgq9WKn5+X0cO4490pNTCbLSQlJSsgiYjkA4UjB5lMJiYs2MHJs5eMHooUckEBvkR2qoWLi0nhSEQkHygc5cLJs5f04FkREZFC5s6YsCEiIiKSTQpHIiIiInYUjkRERETsKByJiIiI2FE4EhEREbFTYMPRxo0bad++PSEhITz66KMsWLDA6CGJiIhIIVAgw9GPP/5Ijx49CA8P58svvyQiIoLRo0ezevVqo4cmIiIiBVyBvM9RXFwcjz76KH379gWgXLly7Nq1i+3bt9OyZUuDRyeSPeaM1Gy1y0i/SnJyMsnJyZjN2XvAq5eXd26GJiJyR8vTcBQcHMywYcNYvnw5+/fvp0KFCvTr149mzZoB10LOtm3bKFmyJBs3buSpp55i6NChfP/990ycOJHffvuN8uXL8/LLL/Pmm2+ybt067rrrLrZv3860adMyrWvMmDG2f2/bto2XX36ZqVOnMmHCBP78809q1qzJu+++ywcffMCyZctwd3ena9eu9OjRIy93gUiWdi/un712wNJp/9ksk717D+V8QDl0pz3f7nakGhhPNTBeXtQgz48cTZgwgcjISMaNG8eSJUvo3bs3CxYs4MEHHwTgp59+omvXrixfvhyz2cz+/fuJiIjgxRdfZOLEiezfv5+YmBhbf8eOHcNiseDq6krfvn356aefKFWqFJ07d6Zjx462dmazmZkzZzJhwgQyMjKIiIigbdu2dOjQgUWLFrFixQqmTJlC06ZNCQ4OzuvdIJKv/P198m1dd8rz7W5nqoHxVAPjObMGeR6O2rdvT6dOnQCIjIzkxx9/ZP78+bZwBNC3b198fX0BGDx4MA888ABRUVEAVKpUiX/++YfRo0cDcPnyZQCGDRvG66+/To8ePdi2bZstQNkHpDfeeIOQkBAA6tevz+7du4mKisJkMhEREcGMGTM4fPiwwpEYIvTpydlqV6mMH+P7PMLFiynZPq2WmHglN0PLFldXF/z8vHI0LnEu1cB4qoHxsqqBn5+Xw0eT8jwc1atXL9P3YWFhbN682fb9XXfdZQtGAPv27aNhw4aZlqlTp47t3+7u7gC0bduWrl27AlC1alWOHTvG3LlzM4Wj8uXL2/7t7e1NUFAQJpMJAE9PTwDS0tJytX0ijnJ1K5Ktdm7unnh7e5OaaiUjI3s/fLPbzhnMZku+rk9upBoYTzUwnjNrkOcnSd3cMucvs9mMi8v/r/Z6SLnO1dUViyXrjStdujQAVapUyfT6vffey8mTJ2+5bvv1ioiIiNxMnqeFPXv2ZPp+165dVK9ePcv2999/P7/88ssNy1wXEBBAuXLl2L17d6Y2hw4doly5ck4YsYiIiNzJ8jwcffzxx6xcuZKjR4/y7rvvcvDgQV588cUs23fr1o09e/YwYcIEjh49ytq1a21Xpl0/Jda7d28+//xzFixYwIkTJ/jss8/44osveOWVV/J6c0RERKSQy/M5R8899xxz587l0KFD3H///XzwwQfcf//9WbavUqUK06dPZ9KkScydO5eKFSvSuXNn4uLiMs03Apg9ezZjx44lMDCQ4cOH065du7zeHBERESnkTFar1ZpXnQcHBzN27Fjat2+f7WV++eUX3NzcqFatmu21lStX8uabb7Jr164b5hEZqd+kDRw5dcHoYUghVzmwGFMGhJOYeOW2mvDp5uaCv7/PbTeuO4lqYDzVwHhZ1aBECR+Hr1a77WYo79+/n65du7Ju3TpOnz7Nli1biIuLo1WrVrdVMBIREZHC6bZLG8888wznzp1jzJgxnD17lrvuuotWrVrZHhUiIiIikpfyNBwdPHgwx8uYTCZ69+5N796982BEIiIiIrd22x05KkiCAnz/u5FILulzJiKSvxSOHGS1WonsVMvoYcgdwmy2YLHk2bUTIiJiR+HIQSaTSc/SMdCd9jwji8WqcCQikk8UjnJBz9IxnmogIiLOdttdyi8iIiJiJIUjERERETs6rZYLjt55U3Lv+r4vaDXQ3CERkdufwpGDrFYrfn5eRg/jjlfQamA2W0hKSlZAEhG5jSkcOchkMjFhwQ5Onr1k9FCkgAgK8CWyUy1cXEwKRyIitzGFo1w4efaSHjwrIiJSyBSsCRsiIiIieUzhSERERMSOwpGIiIiIHYUjERERETu5DkfBwcEsWbLEGWMRERERMZyOHImIiIjYUTgSERERsZOj+xydOXOGmJgYtm7diq+vL4MGDbK9FxwcfNNl+vTpQ+/evUlJSWHcuHF8/fXXpKen88QTT3D16lXc3d0ZN24cS5YsYebMmTRu3JilS5dSr149ZsyYwZEjR4iNjWXXrl1kZGTQqFEjBg8eTGBgIABdunQhMDCQcePG2dZp/9q2bdvo2rUrcXFxjB8/nr///puaNWsydOhQKleu7Mg+k0LGnJGaL+vJSL9KcnIyycnJmM2WPF2Xl5d3nvYvIlKYZTscZWRk8Oqrr1K0aFHmz59PWloaMTExtve///77TO3HjBnD9u3b6dixIwCDBw9m3759TJ48mbvvvpvp06ezZs0a2rVrZ1vm+PHj/PXXXyxbtoyrV69y6tQpnn32WRo2bMjHH39Mamoq48aNo3PnzqxcuZKiRYtme0PHjRvH8OHDKV26NLGxsXTt2pWvv/4aX1/fbPchhdPuxf3zZz3A0mn5sir27j2U5+soqM+3K0xUA+OpBsbLixpkOxxt2bKFw4cPs3btWsqVKwfA2LFjbeGmZMmStrZz587l22+/ZcGCBQQEBHDixAkSEhJ4//33adiwIQCxsbHs3LnzhvX07NmTsmXL2tp4e3szYcIEPDw8AJg2bRrNmjVj+fLldOrUKdsbOnjwYBo3bgzAhAkTCA8P58svv+S5557Ldh8iBYW/v0++raugPd+uMFINjKcaGM+ZNch2ODp06BDFihWzBSOAqlWr4unpmand+vXriY2NZfLkyVSvXh2Affv2ARAWFmZrV6RIEWrUqHHDeipUqJBpnQ888IAtGMG1EFaxYkUOHcrZX8b16tWz/bt48eIO9SGFU+jTk/NlPZXK+DG+zyNcvJiS56fVEhOv5Gn/cO2vND8/r3zZHrk51cB4qoHxsqqBn5+Xw0eTsh2OTCYTFsuNhXdz+/8u9u/fz8CBA+nbty+PPfaY3cBdAW66/L/Zhy2r9eYP57RYLLi7u2fZR0ZGxi3HCWA2m3Fx0WFQAVe3IvmyHjd3T7y9vUlNtZKRkbc/RPO6f3tmsyVf1yc3Ug2MpxoYz5k1yHY6qFq1KpcuXeLw4cO21/744w8uX74MwNmzZ4mIiOCxxx4jIiIi07LBwcGYTCZ+/vln22tpaWn8+uuvt1xncHAwe/bsIS0tzfba33//zbFjx2yTqd3d3W1jgGvB6cSJEzf0tWfPHtu/z58/z7Fjx2xHtkRERESuy3Y4qlevHqGhoURFRfHzzz+zZ88eoqKicHFxISUlhe7du1OmTBkGDhzI33//zblz5zh37hxJSUmULVuWJ554gpEjR7JlyxZ+++033nrrLc6cOYPJZMpync8//zxXrlxh0KBBHDhwgF9++YU33ngDf39/WrVqBUDNmjXZvHkz3333HceOHWPkyJFcvHjxhr5iYmL46aefOHDgAAMHDqRkyZK0aNHCgV0mIiIihVm2T6u5uLgwe/ZsRo0aRbdu3fD09CQiIoJTp07h5eVlm1f08MMPZ1qubt26fPLJJ4wcOZJRo0bRp08frFYrTz75JGFhYbc8PRYUFMT8+fOJjY3l2WefxcPDg0aNGhEbG4ufnx8A3bp14/jx47zxxht4eHjw9NNP06pVqxtOyT377LNERUWRlJRE/fr1mTdvHl5emkAnIiIimZmsWU3scaLU1FQ2bdpE/fr1M11+//jjj9OmTRt69eqVZ+u+fp+jdevWERQU5NS++03awJFTF5zapxRelQOLMWVAOImJVwrF3AQ3Nxf8/X0KzfYURKqB8VQD42VVgxIlfPJ+QnZueHh4EBMTQ926denZsyeurq4sXryY06dP69SWiIiI3Fby5XItk8lEfHw8iYmJPPvsszz11FPs2rWLDz/8UHepFhERkdtKvhw5gmtXu3344Yf5tTqbevXqcfDgwXxfr4iIiBRM+RaOCqOgAD16RLJPnxcRkYJB4chBVquVyE61jB6GFDBmswWLJc+vgRARkVxQOHKQyWTS7eINVFBv2W+xWBWORERucwpHuaDbxRtPNRAREWfTw8VERERE7CgciYiIiNjRabVccPTOm5J71/e9IzXQvB8REbkVhSMHWa1W/Pz0bDajOVIDs9lCUlKyApKIiNyUwpGDTCYTExbs4OTZS0YPRXIgKMCXyE61cHExKRyJiMhNKRzlwsmzl/TgWRERkUJGk2ZERERE7CgciYiIiNhROBIRERGxo3AkIiIiYqdAhqNly5bRsmVLQkJCaNWqFV999ZXRQxIREZFCosCFo+XLl/PWW2/RqVMnvvzyS1q3bs2AAQPYtWuX0UMTERGRQqBAhSOr1crUqVPp2rUrnTp1oly5cvTo0YOGDRvy448/Gj08ERERKQRyHY42btxI+/btCQ0NpUGDBkRHR3PhwgW2bdtGcHAwJ0+etLX992tdunRh6NChdOzYkdq1a7NixQqCg4M5cuRIpnV07dqVyMhIjh49yqlTp3jyySczvf/BBx8QEREBwJIlS2jevDmfffYZ4eHhhIaG0rdvX86ePUtkZCRhYWE88sgjLF68OLebLnnMnJHq9K+M9KskJyeTnJxMSorzvkREpPDI1U0gz58/T+/evYmOjiY8PJwzZ84QFRXF+PHjadOmTbb6WLRoEbGxsQQHB1OyZEmCgoJYuXIl/fr1A+DMmTP89NNPfPDBBxw9ehSA5ORkXnnlFfbt20dQUBA9evSgadOmtj5Pnz7N119/TXx8PH/++Sc9e/Zk69at9OjRg549e/Lhhx/yzjvv0KxZM/z9/XOzCyQP7V7c3/l9AkunOb1b9u495PxOb3O5eb6dOIdqYDzVwHh5UYNchaOzZ8+SlpZGmTJlCAwMJDAwkFmzZmE2m7lwIXt3jq5atWqmI0FPPfUUy5Yts4WjVatWERAQQP369Vm5ciUAgwcPpnfv3kRGRpKQkEDPnj356KOPaNCgAQAZGRkMHTqUypUrU6VKFe6//37c3d15+eWXAXj55ZdZtGgRf/zxh8KROIW/v4/RQzCMnjFoPNXAeKqB8ZxZg1yFo6pVq9K6dWu6d+9OyZIladSoEeHh4TRv3pwdO3Zkq4/y5ctn+r5du3ZMnz6dXbt2ERYWxooVK2jbti0uLi64u7sD8Morr/DUU0/ZxrBv375M4QigXLlytn97e3tzzz332L4vUqQIAGlpaY5tuOSL0KcnO73PSmX8GN/nES5eTMFstjit38TEK07rq6BwdXXBz8/L6ftSsk81MJ5qYLysauDn5+Xw0aRcP1tt4sSJ9OrVi++++44ffviBQYMGUatWLXr27HlDW7PZfMNrnp6emb4PCgqibt26rFy5Eh8fHw4ePEhcXBwAAQEBAFSpUiXTMvfeey8bNmzI9Nr1IHWdi4sOeRY0rm5FnN6nm7sn3t7epKZaychw3g8yZ/ZV0JjNljt6+28HqoHxVAPjObMGuUoMu3fvZsyYMVSqVImXXnqJ+Ph4xowZw9atW21h5PLly7b2f/zxR7b6bd++PWvWrOHLL7/kwQcftB1dql69Oj4+PuzevTtT+0OHDmU6UiQiIiLiqFyFo6JFi7Jw4UJiY2M5duwYhw4dYvXq1VSoUIH7778fb29v4uPjOX78OJs2beKjjz7KVr+PP/44ycnJfPLJJ7Rv3972uqenJ6+++irvvfceq1at4vjx48ycOZPNmzfb5hOJiIiI5EauwlHlypWJi4tj69attGvXjueffx5XV1fmzJmDr68vsbGx7Nu3j5YtWzJ16lQGDx6crX69vLx44oknsFgsPPHEE5ne69mzJ3369GHy5Mm0bNmSr7/+mri4OOrVq5ebTREREREBwGS1Wq1GD6Kg6jdpA0dOZe+qPLk9VA4sxpQB4SQmXtH8gFxyc3PB399H+9JAqoHxVAPjZVWDEiV8HJ6QrVnKIiIiInYUjkRERETsKByJiIiI2FE4EhEREbGT65tA3smCAnyNHoLkkGomIiL/ReHIQVarlchOtYwehjjAbLZgsegiTRERuTmFIweZTCY9S8dAuXmekcViVTgSEZEsKRzlgp6lYzzVQEREnE0TskVERETsKByJiIiI2NFptVxw9LbkknvX931OaqC5RiIikh0KRw6yWq34+XkZPYw7Xk5qYDZbSEpKVkASEZFbUjhykMlkYsKCHZw8e8nooUg2BAX4EtmpFi4uJoUjERG5JYWjXDh59hJHTl0wehgiIiLiRJo0IyIiImJH4UhERETEjsKRiIiIiB2FIxERERE7+RKOgoODWbJkiVP7bNq0KXFxcU7tU0RERERHjkRERETs6FJ+uW2YM1LzrO+M9KskJyeTnJyM2ez8B9V6eXk7vU8RETGG08PRmTNniImJYevWrfj6+jJo0CDbe3FxcezYsYOGDRsyf/58EhMTCQ0NJSYmhsqVKwPXTsH16tWLpUuXkp6ezvz587nrrrsYNWoU69atw83NjYiIiBvWu2jRIubNm8exY8dwcXGhWrVqDBkyhJCQED7++GOmTJnCDz/8gJfXtTsqWywWwsPDiYiIoFOnTs7eDeKA3Yv7513fwNJpedY9e/ceyrvOb1OOPMJFnEs1MJ5qYLy8qIFTw1FGRgavvvoqRYsWZf78+aSlpRETE5Opzfbt2ylSpAjx8fGkp6cTFRVFTEwM8+bNs7VZuHAhc+bMwWw2U6FCBV555RVOnz7NrFmz8PHxYdy4cZw6dcrWfu3atYwYMYJRo0ZRu3Ztzp07x8iRI3n77bdZvnw5Tz75JLGxsaxZs4a2bdsC8MMPP5CYmEjr1q2duQvkDuXv72P0EAyjx+gYTzUwnmpgPGfWwKnhaMuWLRw+fJi1a9dSrlw5AMaOHUu7du1sbTIyMhg/fjzFihUD4LnnniM2NjZTP23btiUkJASA33//ne+//565c+dSu3ZtACZOnEiTJk1s7YsXL87o0aNp06YNAIGBgTz99NOMGDECgBIlStC0aVNWrFhhC0dLly6ladOmtnGI8UKfnpxnfVcq48f4Po9w8WJKnpxWS0y84vQ+b3euri74+Xnl2T6V/6YaGE81MF5WNfDz83L4aJJTw9GhQ4coVqyYLRgBVK1aFU9PT9v3d999d6ZA4uvrS3p6eqZ+ypcvn6lPwBaWrvdRtmxZ2/d16tThyJEjvPfee/z+++8cO3aMgwcPYrH8/07q0KEDPXr04K+//sLb25tvvvmGadPy8DyL5JirW5E869vN3RNvb29SU61kZDj/B1he9FlQmM2WO3r7bweqgfFUA+M5swZOPUlqMpkyBZLr3Nz+P4N5eHj8Zz/2YcpkMgHc0K99nytXrqRNmzacOHGCBx98kMGDBxMdHZ2p/UMPPcTdd9/NqlWrWLNmDX5+fjz00EPZ2zARERG5Yzj1yFHVqlW5dOkShw8f5r777gPgjz/+4PLly7nqE2Dnzp2Eh4cDcPHiRY4fP25rEx8fz9NPP51pftO6desAsFqtmEwmXF1dadeuHWvXrsXPz4+2bdvi6urq8LhERESkcHJqOKpXrx6hoaFERUUxfPhwXF1dGTlyJC4ujh+gKleuHC1atGDEiBF4eHhw9913M2nSJNLS0mxt7rnnHnbu3Mmvv/6Kr68v69evZ/78+QCkpaVRpMi10zXt27fn/fffx9XVlaioqNxtrIiIiBRKTj2t5uLiwuzZs6lUqRLdunUjIiKCVq1aUaJEiVz1++6779K4cWP69+9Pp06duPfee3nggQds7w8dOpS7776bzp0707FjR7799lvGjx8PwJ49e2ztKlSoQGhoKNWqVbPdOkBERETEnslqtVqNHkR+sVqtPProo3Tv3p2OHTvmur9+kzZw5NQFJ4xM8lrlwGJMGRBOYuIVTZp0Ejc3F/z9fbRPDaQaGE81MF5WNShRwuf2uFrtdpWens769evZunUrycnJtGrVyughiYiIyG3qjghH7u7ujBo1CoDY2Fi8vfWoBxEREbm5OyIcAWzatMnoIYiIiEgBcMeEo7wQFOBr9BAkm1QrERHJLoUjB1mtViI71TJ6GJIDZrMFi+WOuf5AREQcpHDkIJPJpGfpGMiR5xlZLFaFIxER+U8KR7mgZ+kYTzUQERFnc+pNIEVEREQKOoUjERERETs6rZYLjt55U/6b5geJiIhRFI4cZLVa8fPzMnoYhZbZbCEpKVkBSURE8p3CkYNMJhMTFuzg5NlLRg+l0AkK8CWyUy1cXEwKRyIiku8UjnLh5NlLevCsiIhIIaNJMyIiIiJ2FI5ERERE7CgciYiIiNhROBIRERGx4/RwFBwczJIlS3LVx7Zt2wgODubkyZNOGpWIiIhI9ujIkYiIiIgdhSMRERERO7m6z9GZM2eIiYlh69at+Pr6MmjQINt7wcHBN12mT58+9O7dm/T0dGbMmMGyZcs4f/48lStXZuDAgTRq1OiGZS5cuEBsbCwbN27k/Pnz+Pn50axZM9566y28vK7dpfqDDz7g008/5cyZM5QqVYoOHTrQs2dPTCYTKSkpjBo1ig0bNnDx4kUqV65Mz549eeyxx3Kz+ZJN5ozUHLXPSL9KcnIyycnJmM2Wm7ZxdXWhSBHTDW28vLxzNVYRERGHw1FGRgavvvoqRYsWZf78+aSlpRETE2N7//vvv8/UfsyYMWzfvp2OHTsCMHr0aBISEhg+fDjVqlXjiy++oHv37ixfvvyGdUVHR3P27FmmT5/OXXfdxc6dO3nzzTe59957eemll1i/fj2zZ89m8uTJVKxYkZ9//pmoqCiCgoJo27YtU6dO5eDBg8THx+Pn58eiRYvo378/CQkJBAUFOboLJJt2L+6fs/bA0mmOrWvv3kOOLSg5dv3ZgnrGoHFUA+OpBsbLixo4HI62bNnC4cOHWbt2LeXKlQNg7NixtGvXDoCSJUva2s6dO5dvv/2WBQsWEBAQwOXLl1m8eDFDhw6lRYsWAPTv3x+r1crly5dvWFejRo2oU6eO7WhUUFAQ8+fP59Cha78Ijx8/joeHB4GBgZQpU4YyZcpQqlQpypQpY3vfx8eHsmXL4ufnxxtvvEGdOnUoVqyYo5svtyl/fx+jh3DH0TMGjacaGE81MJ4za+BwODp06BDFihWzBSOAqlWr4unpmand+vXriY2NZfLkyVSvXh2Ao0ePkp6eTmhoaKa2AwYMAK5drWbvhRdeYP369SxdupQ//viD3377jZMnT1KpUiUA2rRpwxdffMHjjz/OvffeS8OGDXn88cdt4ei1116je/fuNGjQgBo1atCoUSOefPJJfH19Hd18yYHQpyfnqH2lMn6M7/MIFy+m3PK0mp+f1w1tEhOv5Gqskn1Z1UDyj2pgPNXAeFnVwM/Py+GjSQ6HI5PJhMVy4wfBze3/u9y/fz8DBw6kb9++meb3uLu7Z3s9FouFiIgIDh8+TOvWrWnZsiXVq1dn6NChtjYlSpRg+fLl7Nq1i82bN/P9998zb9482/ymsLAwNm7cyObNm9myZQvLli1j5syZvP/++zRo0MDBPSDZ5epWJEft3dw98fb2JjXVSkbGzX/YuLm53LRNVu0l75jNFu13g6kGxlMNjOfMGjh8gq5q1apcunSJw4cP2177448/bKfFzp49S0REBI899hgRERGZli1fvjzu7u7s2bMn0+vPPPMMc+fOzfTa/v37+e6775g6dSqRkZG0adOGcuXKcfz4cazWa09sX7FiBZ9++im1atWib9++/O9//6Njx46sXr0agGnTprFjxw6aNWvG22+/TUJCAmXLliUhIcHRzRcREZFCyuEjR/Xq1SM0NJSoqCiGDx+Oq6srI0eOxMXFhZSUFLp3706ZMmUYOHAgf//9ty3IuLu7U7x4cTp37szUqVMpUaIE9913H4sXL+bQoUOMGzeOc+fO2dZz99134+bmxldffUWJEiVISkpi1qxZnDt3jrS0NABSU1N599138fHxoXbt2pw5c4affvqJ2rVrA3DixAlWrFjByJEjKVeuHLt37+b06dOEhYXlZt+JiIhIIeRwOHJxcWH27NmMGjWKbt264enpSUREBKdOncLLy4t9+/YB8PDDD2darm7dunzyyScMGDAAV1dXhg8fzqVLl7j//vuJj4+nUqVKmcJRQEAA48aNIy4ujgULFlCyZEnCw8NtV6kBdOzYkaSkJGbMmMGff/5JsWLFePzxx4mMjARg+PDhvPvuuwwaNIikpCQCAwOJjIykbdu2jm6+iIiIFFIm6/VDOpJj/SZt4MipC0YPo9CpHFiMKQPCSUy8css5R/7+PrdsI3lLNTCeamA81cB4WdWgRAkfhydk68YMIiIiInYUjkRERETsKByJiIiI2MnVs9XudEEBuolkXtB+FRERIykcOchqtRLZqZbRwyi0zGYLFouuFRARkfyncOQgk8mk28XnIYvFqnAkIiKGUDjKBd0uXkREpPDRhGwREREROwpHIiIiInZ0Wi0XHL3zptyc5hmJiMjtQOHIQVarFT8/L6OHUaiYzRaSkpIVkERExFAKRw4ymUxMWLCDk2cvGT2UQiEowJfITrVwcTEpHImIiKEUjnLh5NlLevCsiIhIIaNJMyIiIiJ2FI5ERERE7CgciYiIiNhROBIRERGx47RwdPr0ab788stst//222/57bffnLX6HNuxYwfbt283bP0iIiJye3JaOBo8eDCbNm3KVttTp07RvXt3/vnnH2etPsdeeOEFjh8/btj6RURE5PZkyGk1q1X3sREREZHbk1PCUZcuXfjxxx9ZunQpTZs25erVq0yZMoVmzZoREhJC27ZtSUhIAODkyZM0a9YMgK5duxIXF8e2bduoVq0aa9eu5fHHH6dGjRp07dqVP//8k1GjRlG7dm0aNGjAzJkzM613xYoVtGnThho1atCsWTM+/vhj23sbN26kffv2hIaG0qBBA6Kjo7lw4do9iYKDgwEYMmQI0dHRztgFkgVzRmq2vjLSr5KcnExycjIpKbf+EhERyUsmqxMO4yQlJdG9e3dKly7NsGHDePvtt9m3bx/vvPMO5cuXZ9WqVbz33ntMnz6dJk2a8Ouvv9KxY0fi4uJo1KgRe/fupWvXrlSvXp2YmBgyMjKIiIgAoEOHDjzzzDOsWLGCGTNmsGLFCoKDg1m9ejUDBw4kMjKSZs2a8euvvxIdHU1MTAzh4eE0btyY6OhowsPDOXPmDFFRUdSvX5/Ro0dz7tw5HnroId58803at2+Pr6+vQ9vdb9IG3QTyP+z8rKfT+9y79xCuri74+Xlx8WIKZrPF6euQ/6YaGE81MJ5qYLysauDn5+XwM1Cdcofs4sWL4+7ujqenJ4mJiaxbt45Zs2YRHh4OQJ8+fThw4ACzZs3i0UcfpUSJEgAUK1YMHx8fWz9vvPEGISEhANSvX5/du3cTFRWFyWQiIiKCGTNmcPjwYYKDg/n4449p2bIlr7zyCgAVKlTgypUreHp6cvbsWdLS0ihTpgyBgYEEBgYya9YszGYzACVLlgTA19fX4WAkxvH3///PjJ5vZzzVwHiqgfFUA+M5swZOf3zIwYMHAahVq1am1+vUqcOkSZNuuWz58uVt//b29iYoKAiTyQSAp6cnAGlpaQAcOnSIVq1aZVr+mWeesf27devWdO/enZIlS9KoUSPCw8Np3ry5g1sljgp9enK22lUq48f4Po9k66+vxMQr+mvtNqAaGE81MJ5qYLzb9shRdlitVtzcbr26f7/v4pL1Rv1XXxMnTqRXr1589913/PDDDwwaNIhatWplmpckec/VrUi22rm5e+Lt7U1qqpWMjFv/gLF/32y2/Gd7yVuqgfFUA+OpBsZzZg2cfrXa9cnOO3bsyPT69u3buffeewFsR4Nyo3LlyuzZsyfTa2PHjqVv377s3r2bMWPGUKlSJV566SXi4+MZM2YMW7duNfT2ASIiInL7c9qRIx8fH06dOoWPjw9NmjQhJiYGk8lE+fLl+fLLL1m3bh1TpkwBrp0yg2unxqpVq+bQ+l5//XX69OlDjRo1aNy4Mbt37+bTTz9lxIgRFC1alIULF+Lu7s4zzzxDamoqq1evpkKFCvj7+9vGcOTIERITE22viYiIiDgtHD333HMMHjyYNm3asGHDBiZNmsRbb73FxYsXqVKlCnFxcbY5P/7+/nTo0IHx48dz7Ngxh+YCNW3alBEjRjBnzhzeffddAgMDGTJkCO3atQMgLi6O6dOns3DhQlxcXKhfvz5z5syxnarr1q0b77//PkeOHGHWrFnO2g0iIiJSwDnlUv47lS7ld57KgcWYMiCcxMQr2Tpn7Obmgr+/T7bbi/OpBsZTDYynGhgvqxqUKOHj8IRsPXhWRERExI7CkYiIiIgdhSMREREROwpHIiIiInby7SaQhVFQgB494izalyIicrtQOHKQ1WolslOt/24o2WY2W7BYdPGkiIgYS+HIQSaTSc/ScTKLxapwJCIihlM4ygU9S0dERKTw0YRsERERETsKRyIiIiJ2dFotFxy9LblofpGIiNy+FI4cZLVa8fPzMnoYBZbZbCEpKVkBSUREbjsKRw4ymUxMWLCDk2cvGT2UAicowJfITrVwcTEpHImIyG1H4SgXTp69xJFTF4wehoiIiDiRJs2IiIiI2FE4EhEREbGjcCQiIiJiR+FIRERExE6BCkdxcXE0bdrU9n1wcDBLliwxcEQiIiJS2BSocCQiIiKS13Qpv+QJc0Zqlu9lpF8lOTmZ5ORkzOabP7jXy8s7r4YmIiJyS4aGo0OHDjFx4kR27txJSkoKAQEBdOrUiW7dugHw+eef8/7773P27FkaNmxIUFBQln2lpKQwatQoNmzYwMWLF6lcuTI9e/bkscceA67d0XrevHksXLiQP//8k7Jly9KjRw9at26dL9t6p9m9uH/W7wFLp916+b17D93y/euPbtEjXIyjGhhPNTCeamC8vKiBYeEoJSWFbt260ahRIz777DNcXV1ZtGgR7777Lg0aNODIkSOMGDGCN998k4YNG7J27VomT57MPffcc9P+pk6dysGDB4mPj8fPz49FixbRv39/EhISCAoK4v333+e9997jrbfeol69emzcuJGoqCjuvvtu6tevn89bL//F398nW+30CBfjqQbGUw2MpxoYz5k1MDQcde3alU6dOuHjc+0XYd++fXn//fc5ePAgn376KS1btqRTp04AvP766/z8888cOHDgpv0dP34cHx8fypYti5+fH2+88QZ16tShWLFiWK1WPv74Y7p27UrHjh0B6NKlC1evXiUjIyN/NvgOE/r05Czfq1TGj/F9HuHixZQsT6slJl65Zf+uri74+Xndsg/JW6qB8VQD46kGxsuqBn5+Xg4fTTIsHJUoUYIXXniBVatWsW/fPo4fP24LPhaLhUOHDtGqVatMy4SFhWUZjl577TW6d+9OgwYNqFGjBo0aNeLJJ5/E19eX8+fPc+7cOUJDQ29YRvKGq1uRLN9zc/fE29ub1FQrGRk3/2GS1ev/ZjZbst1W8oZqYDzVwHiqgfGcWQPDTpKeO3eONm3asGjRIgICAnjhhRdYunRppjYWS+aNdHd3z7K/sLAwNm7cyLRp06hevTrLli2jZcuWbNmy5ZbLiYiIiNgzLBytWrWKpKQkPv30U3r27Enz5s25cOHaQ1ytVitVq1Zl586dmZbZs2dPlv1NmzaNHTt20KxZM95++20SEhIoW7YsCQkJ+Pr6UqpUqRuW79u3L2PHjnX+xomIiEiBZVg4Kl26NCkpKXz99decPn2a77//ngEDBgCQlpbG66+/ztq1a3n//ff5448/+OSTT0hISMiyvxMnTjB8+HC2bNnCqVOnSEhI4PTp04SFhQHX5ix9/PHHLF++nOPHjzNv3jzWrVtHs2bN8mV7RUREpGAwbM5RixYt+PXXXxk3bhyXL18mMDCQjh07sm7dOvbs2cPzzz/PxIkTiYuLY+rUqdSsWZNu3bqxatWqm/Y3fPhw3n33XQYNGkRSUhKBgYFERkbStm1bADp37szVq1eZOnUq586do0KFCkyePJm6devm52aLiIjIbc5ktVqtRg+ioOo3aQNHTl0wehgFTuXAYkwZEE5i4hWHJ8+5ubng7++Tqz4kd1QD46kGxlMNjJdVDUqU8HH4ajXdtUpERETEjsKRiIiIiB2FIxERERE7evBsLgQF+Bo9hAJJ+01ERG5nCkcOslqtRHaqZfQwCiyz2YLFomsBRETk9qNw5CCTyaRn6eSCxWJVOBIRkduSwlEu6Fk6IiIihY8mZIuIiIjYUTgSERERsaPTarng6J0370SaYyQiIgWFwpGDrFYrfn5eRg+jwDCbLSQlJSsgiYjIbU/hyEEmk4kJC3Zw8uwlo4dy2wsK8CWyUy1cXEwKRyIicttTOMqFk2cv6cGzIiIihYwmzYiIiIjYUTgSERERsaNwJCIiImJH4UhERETEToEMR0lJSQwbNoxHHnmEBx98kOeff57t27cbPSwREREpBApkOBowYAC7du1i0qRJfPHFF1StWpVXXnmF33//3eihiYiISAFX4MLRsWPH2Lx5M++88w61a9emYsWKDB06lFKlSrFy5UqjhyciIiIFnFPuc7Rx40amTp3KkSNH8Pb2pnHjxgwZMoQDBw7QtWtX1q1bR1BQEADbtm3L9FqXLl2oUKECBw4c4OjRowwbNoxBgwaxevVqKleubFtH165dKVWqFMOGDSM+Pp6QkBDbeyaTCZPJxMWLFwGIjo7GYrHg5+fHsmXLcHFxoXPnzrRq1YqhQ4eyd+9eypcvz6hRowgNDXXGLiiUzBmpTuknI/0qycnJJCcnYzZbnNKnr29Rp/QjIiLyb7kOR+fPn6d3795ER0cTHh7OmTNniIqKYvz48bRp0yZbfSxatIjY2FiCg4MpWbIkQUFBrFy5kn79+gFw5swZfvrpJz744AP8/Pxo3LhxpuUTEhI4duwYb775pu211atX06lTJ5YsWcKqVauYOnUqK1euJDo6mqCgIN566y1iYmJYsmRJbndBobV7cX/n9AMsneaUrmz27/8N0PPtjHR936sGxlENjKcaGC8vapDrcHT27FnS0tIoU6YMgYGBBAYGMmvWLMxmMxcuZO/u0VWrVuXJJ5+0ff/UU0+xbNkyWzhatWoVAQEB1K9f/4Zld+7cyZAhQ3jssccIDw+3vV68eHEGDx6Mi4sLL730ElOnTqVly5Y0a9YMgPbt2zNmzBjHN1wMdf25dnq+nfFUA+OpBsZTDYznzBrkOhxVrVqV1q1b0717d0qWLEmjRo0IDw+nefPm7NixI1t9lC9fPtP37dq1Y/r06ezatYuwsDBWrFhB27ZtcXHJnAq/+eYbIiMjefDBB5kwYUKm94KCgmztvb29AShbtqztfU9PT9LT03O8vXeS0KcnO6WfSmX8GN/nES5eTHHaabWLF1Pw8/Nyap+SM66uLqqBwVQD46kGxsuqBn5+Xg4fTXLKnKOJEyfSq1cvvvvuO3744QcGDRpErVq16Nmz5w1tzWbzDa95enpm+j4oKIi6deuycuVKfHx8OHjwIHFxcZnazJ8/n9GjR9OiRQveffddPDw8Mr3v7u5+w3r+Ha7k1lzdijilHzd3T7y9vUlNtZKR4ZwfHtf/A5jNFqf1KY5RDYynGhhPNTCeM2uQ67Swe/duxowZQ6VKlXjppZeIj49nzJgxbN261RZGLl++bGv/xx9/ZKvf9u3bs2bNGr788ksefPDBTEeXFi5cyMiRI+nUqROTJk26IRiJiIiIOCrX4aho0aIsXLiQ2NhYjh07xqFDh1i9ejUVKlTg/vvvx9vbm/j4eI4fP86mTZv46KOPstXv448/TnJyMp988gnt27e3vX706FHGjBlD8+bNiYiI4O+//+bcuXOcO3eOS5cu5XZzRERE5A6X63BUuXJl4uLi2Lp1K+3ateP555/H1dWVOXPm4OvrS2xsLPv27aNly5ZMnTqVwYMHZ6tfLy8vnnjiCSwWC0888YTt9YSEBNLT01m7di0PPfRQpq/Ro0fndnNERETkDmeyWq1WowdRUPWbtIEjp7J3Rd6drHJgMaYMCCcx8YrTzge7ubng7+/j1D4lZ1QD46kGxlMNjJdVDUqU8HF4QrZmKIuIiIjYUTgSERERsaNwJCIiImLHKfc5ulMFBfgaPYQCQftJREQKEoUjB1mtViI71TJ6GAWG2WzBYtHcfxERuf0pHDnIZDLpdvE5YLFYFY5ERKRAUDjKBd0uXkREpPDRhGwREREROwpHIiIiInYUjkRERETsKByJiIiI2FE4EhEREbGjcCQiIiJiR+FIRERExI7CkYiIiIgdhSMREREROwpHIiIiInYUjkRERETsmKxWq54G6iA9dNZYrq4uqoHBVAPjqQbGUw2Md7MauLiYMJlMDvWncCQiIiJiR6fVREREROwoHImIiIjYUTgSERERsaNwJCIiImJH4UhERETEjsKRiIiIiB2FIxERERE7CkciIiIidhSOREREROwoHImIiIjYUTgSERERsaNwJCIiImJH4UhERETEjsLRTVgsFqZNm8bDDz9MzZo1ee211zhx4kSW7RMTExk4cCB16tShbt26xMTEkJKSko8jLnxyWoPDhw/z+uuvU69ePRo0aEDfvn05ffp0Po648MlpDeytWLGC4OBgTp48mcejLNxyWoP09HQmTpxoa9+5c2f279+fjyMufHJag3/++YeBAwdSv3596tWrR//+/Tl79mw+jrhwmz17Nl26dLllG2f8TlY4uokZM2awcOFCRo4cyWeffYbFYuHVV18lLS3tpu379u3LsWPHmDt3LlOnTmXjxo288847+TvoQiYnNUhMTOTll1/G09OTTz75hDlz5nD+/HleffVVUlNTDRh94ZDT/wfXnTp1ihEjRuTTKAu3nNbgnXfeYcmSJYwZM4YvvviCEiVK8Nprr3Hp0qV8HnnhkdMa9OvXj9OnT/PRRx/x0Ucfcfr0aXr16pXPoy6cFixYwJQpU/6znVN+J1slk9TUVGtYWJh1wYIFttcuXLhgrVGjhnXlypU3tN+5c6e1SpUq1t9++8322qZNm6zBwcHWM2fO5MuYC5uc1uB///ufNSwszJqSkmJ77fTp09YqVapYf/jhh3wZc2GT0xpcZzabrc8//7y1a9eu1ipVqlhPnDiRH8MtlHJag+PHj1uDg4Ot3377bab2TZo00f8DB+W0BhcuXLBWqVLFum7dOttr33zzjbVKlSrWxMTE/BhyoXTmzBlrRESEtWbNmtYWLVpYO3funGVbZ/1O1pGjfzlw4ABXrlyhQYMGttf8/PyoVq0aP/300w3tt2/fTsmSJalcubLttbp162IymdixY0e+jLmwyWkNGjRowIwZM/D09LS95uJy7aN98eLFvB9wIZTTGlw3a9Ys0tPTiYiIyI9hFmo5rcHmzZvx9fXlkUceydR+/fr1mfqQ7MtpDTw9PfHx8WHZsmVcvnyZy5cvs3z5cipWrIifn19+Dr1Q+fXXX3F3d2fFihWEhobesq2zfie7OTzaQurMmTMA3HPPPZleL1WqlO09e2fPnr2hrYeHB8WLF+fPP//Mu4EWYjmtQVBQEEFBQZlei4+Px9PTkzp16uTdQAuxnNYA4JdffuHDDz9k8eLFmmPhBDmtwdGjRylbtixr1qwhPj6es2fPUq1aNaKjozP9opDsy2kNPDw8GDduHMOGDaN27dqYTCZKlSrF/PnzbX+wSc41bdqUpk2bZquts34nq1r/cn3SloeHR6bXixQpctP5KykpKTe0vVV7+W85rcG/ffLJJ8yfP5/IyEhKlCiRJ2Ms7HJag+TkZCIjI4mMjKRChQr5McRCL6c1uHz5MseOHWPGjBkMGDCAmTNn4ubmxgsvvMA///yTL2MubHJaA6vVyv79+wkLC2PBggV8/PHHlClThp49e3L58uV8GfOdzlm/kxWO/uX6qZl/T7ZLTU3Fy8vrpu1vNjEvNTUVb2/vvBlkIZfTGlxntVqZMmUKo0aNokePHv95RYNkLac1GDVqFBUrVuS5557Ll/HdCXJaAzc3Ny5fvszkyZN56KGHqFGjBpMnTwZg6dKleT/gQiinNfjqq6+YP38+sbGx1KpVi7p16zJr1ixOnTrF4sWL82XMdzpn/U5WOPqX64fj/vrrr0yv//XXXwQEBNzQvnTp0je0TUtLIykpiVKlSuXdQAuxnNYArl3CPGjQIGbNmsWQIUPo169fXg+zUMtpDb744gt++OEHwsLCCAsL47XXXgOgdevWzJo1K+8HXAg58rPIzc0t0yk0T09PypYtq1sqOCinNdi+fTsVK1akaNGitteKFStGxYoVOXbsWN4OVgDn/U5WOPqX+++/n6JFi7Jt2zbbaxcvXmTfvn03nb9Sp04dzpw5k+mD/+OPPwJQq1atvB9wIZTTGgBERUXx9ddfM3HiRF566aV8GmnhldMarFmzhlWrVrFs2TKWLVvGqFGjgGtzv3Q0yTGO/CzKyMhgz549tteuXr3KiRMnKF++fL6MubDJaQ1Kly7NsWPHMp2+SU5O5uTJkzrdnE+c9TtZE7L/xcPDg86dOzNhwgRKlChBYGAgsbGxlC5dmsceewyz2cz58+fx9fXF09OT0NBQHnzwQfr3788777xDcnIyw4YNo127dlke5ZBby2kNlixZwurVq4mKiqJu3bqcO3fO1tf1NpIzOa3Bv3/5Xp+sWqZMGYoXL27AFhR8Oa1B7dq1adiwIYMHD2bEiBEUL16cadOm4erqStu2bY3enAIppzVo164dH3zwAf369eONN94AYMqUKRQpUoT27dsbvDWFU579Ts7FrQcKrYyMDOv48eOt9evXt9asWdP62muv2e7XcuLECWuVKlWsX3zxha3933//be3Tp4+1Zs2a1nr16lmHDx9uvXr1qlHDLxRyUoOXX37ZWqVKlZt+2ddJcian/w/sbd26Vfc5coKc1uDSpUvW4cOHW+vVq2cNDQ21vvzyy9bDhw8bNfxCIac1+O2336wRERHWunXrWuvXr2/t3bu3/h840eDBgzPd5yivfiebrFarNe8ynYiIiEjBojlHIiIiInYUjkRERETsKByJiIiI2FE4EhEREbGjcCQiIiJiR+FIRERExI7CkYiIiIgdhSMREREROwpHIiIiInYUjkRERETsKByJiIiI2Pk/YlODR50fnnQAAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.plot_feature_importances(eval_times=365)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Similarly we can look at some shape functions related to mortality risk in the next year." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.plot_shape_function(feature_names=[\"dnr\", \"avtisst\", \"ca\"], eval_times=365)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's look at each of these features to see if the resulting shape functions makes sense:\n", "- **dnr**: this feature indicates if the patients has a do not resuscitate order or not. It makes sense that patients are at higher risk of imminent mortality risk if they have dnr orders.\n", "- **avtisst**: this feature indicates the average TISS score, where higher TISS scores indicate higher intensity care in the ICU. It's again natural that patients receiving higher intensity care are at higher mortality risk.\n", "- **ca**: this feature indicates if the patient has local cancer (yes), cancer that has spread (metastatic), or does not have cancer at all (no). It's well known that metastatic cancer prevents higher mortality risk, which is reflected in the learned shape function." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How would the results change with a different evaluation time? Let's look at the feature importances and some shape functions for mortality risk in the next 30 days instead of in the next year." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.plot_feature_importances(eval_times=30)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.plot_shape_function(feature_names=[\"dnr\", \"avtisst\", \"ca\"], eval_times=30)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Interestingly, avtisst becomes more important than dnr for 30-day mortality. One explanation is that increased TISS scores can indicate very immediate mortality risk (e.g. increased mechanical ventilation, monitoring), while a do not resuscitate order do not imply as immediate mortality risk. Otherwise, the shape of the shape functions remain very similar." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Calibration\n", "\n", "It's important that the survival/CIF estimates from a survival analysis model are calibrated. A survival analysis model is calibrated if \n", "for all $t > 0$ and all sets $S = \\{i \\,:\\, \\hat{P}(T \\leq t \\mid X^{(i)}) \\approx \\alpha\\}$ we have\n", "$$\n", "\\alpha \\approx \\hat{P}(T \\leq t \\mid X^{(i)})\n", "\\approx \\sum_{i\\in S} \\frac{1_{T^{(i)} \\leq t}}{|S|}.\n", "$$\n", "That is, when the model predicts $\\hat{P}(T \\leq t \\mid X^{(i)})$, this prediction can be interpreted in the correct probabilistic sense. There are multiple ways to check calibration for a survival analysis model, but we recommend assessing calibration via visual inspection of calibration plots as described in [1]. DNAMite can easily produce such a calibration plot.\n", "\n", "Austin, Peter C., Frank E. Harrell Jr, and David van Klaveren. \"Graphical calibration curves and the integrated calibration index (ICI) for survival models.\" Statistics in Medicine 39.21 (2020): 2714-2742." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "model.make_calibration_plot(X_test, y_test, eval_times=365)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It's clear from this plot that our trained model is well calibrated." ] } ], "metadata": { "kernelspec": { "display_name": "jss (3.9.6)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.6" } }, "nbformat": 4, "nbformat_minor": 2 }