SURVIVAL AND LIFE TABLES - PowerPoint PPT Presentation

SURVIVAL AND LIFE TABLES

Nigel Paneth

1. AGE (x)

2. AGE-SPECIFIC MORTALITY RATE (qx)

3. NUMBER ALIVE AT BEGINNING OF YEAR (lx)

4. NUMBER DYING IN THE YEAR (dx)

We use column 2 multiplied by column 3 to obtain column 4.

Then column 4 is subtracted from column 3 to obtain the next row’s entry in column 3.

100,000 births ( row 1, column 3) have an infant mortality rate of 46.99/thousand (row 2, column 2), so there are 4,699 infant deaths (row 3, column 4). This leaves 95,301 left (100,000 – 4,699) to begin the second year of life (row 2 column 3).

e.g. in this table, we see that 90.27% of non-white males survived to age 30.

Column:

• THE NUMBER OF YEARS LIVED BY THE POPULATION IN YEAR X (Lx)
• THE NUMBER OF YEARS LIVED BY THE POPULATION IN YEAR X AND IN ALL SUBSEQUENT YEARS (Tx)
• THE LIFE EXPECTANCY FROM THE BEGINNING OF YEAR X (ex)

The total number of years lived in each year is listed in column 5, Lx.It is based on two sources. One source is persons who survived the year, who are listed in column 3 of the row below. They each contributed one year. Each person who died during the year (column 4 of the same row) contributed a part of year, depending on when they died. For most purposes, we simply assume they contributed ½ a year.

• 94,291 children survived to age 9 (column 3 of age 9-10), contributing 94,921 years.
• 60 children died (column 4 of age 8-9) , so they contributed ½ year each, or 30 years.
• 94,921 + 30 = 94,321.

Because deaths in year 1 are not evenly distributed during the year (they are closer to birth), infants deaths contribute less than ½ a year.

Can you figure out what fraction of a year are contributed by infant deaths (0-1) in this table?

• 95,301 contributed one year
• 96,254 - 95,301 = 953 years, which must come from infants who died 0-1
• 4,699 infants died 0-1
• 953/4,699 = .202 or 1/5 of a year, or about 2.4 months

The top line of Column 6, or Tx=0, is obtained by summing up all of the rows in column 5. It is the total number of years of life lived by all members of the cohort.

This number is the key calculation in life expectancy, because, if we divide it by the number of people in the cohort, we get the average life expectancy at birth, ex=0, which is column 7.

For any year, column 6, Tx, provides the number of years yet to be lived by the entire cohort, and column 7, the number of years lived on average by any individual in the cohort. (Tx/lx)

Thus column 7 is the final product of the life table, life expectancy at birth, or life expectancy at any other specified age.

Life expectancy at birth in the US now is 77.3 years. This means that a baby born now will live 77.3 years if…………..

that baby experiences the same age-specific mortality rates as are currently operating in the US.

• Median survival. Duration of time until 50% of the population dies.
• Relative survival. 5-year survival in the group of interest/5-year survival in all people of the same age.
• Observed Survival.A life table approach to dealing with censored data from successive cohorts of people. Censoring means that information on some aspect of time or duration of events of interest is missing.

• Right censoring
• Left censoring
• Interval censoring

Censoring means that some important information required to make a calculation is not available to us. i.e. censored.

Right censoring is the most common concern. It means that we are not certain what happened to people after some point in time. This happens when some people cannot be followed the entire time because they died or were lost to follow-up.

Left censoring is when we are not certain what happened to people before some point in time.Commonest example is when people already have the disease of interest when the study starts.

Interval censoring is when we know that something happened in an interval (i.e. not before time x and not after time y), but do not know exactly when in the interval it happened. For example, we know that the patient was well at time x and was diagnosed with disease at time y, so when did the disease actually begin? All we know is the interval.

Since right censoring is the commonest problem, lets try to find out what 5-year survival is now for people receiving a certain treatment for a disease.

Number Number alive in

Treated 1999 00 01 02 03

1999 84 44 21 13 10 8

2000 62 31 14 10 6

2001 93 50 20 13

2002 60 29 16

2003 76 43

Total 375

We have 5 years of survival data only from the first cohort, those treated in 1999.

For each successive year, our data is more right-censored. By 2003, we have only one year of follow-up available.

It is:

(44 + 31 + 50 + 29 + 43 = 197)/375 = 52%

Number Number alive in

Treated 99 00 01 02 03

1999 84 44 21 13 10 8

2000 62 31 14 10 6

2001 93 50 20 13

2002 60 29 16

2003 76 43

Total 375

(21 + 14 + 20 + 16 = 71)/154 = 46%

Note that 154 is also 197 (last slide’s numerator) – 43, the number for whom we have only one year of data

Number Number alive in

Treated 96 97 98 99 00

1995 84 4421 13 10 8

1996 62 3114 10 6

1997 93 5020 13

1998 60 2916

1999 76 43

Total 375

(13 + 10 + 13 = 36)/(71 - 16 = 55) = 65%

 Number Number alive in

Treated 99 00 01 02 03

1999 84 44 2113 10 8

2000 62 31 1410 6

2001 93 50 2013

2002 60 29 16

2003 76 43

Total 375

In year 5, survival is 8/16-6 = 80%

Number Number alive in

Treated 99 00 01 02 03

1999 84 44 21 13108

2000 62 31 14 10 6

2001 93 50 20 13

2002 60 29 16

2003 76 43

Total 375

.54 x .46 x .65 x .70 x .80 = .08 or 8.8%

2 year survival = .54 x .46 = .239 or 23.9%

1999 - 52.3%

2000 - 50.0%

2001 - 53.7%

2002 - 48.3%

2003 - 56.6%

Little difference is apparent.